Director_Sivaji_Bandyopadhyay

Professor Sivaji Bandyopadhyay

Director, NIT Silchar

 

Professor Sivaji Bandyopadhyay obtained his Bachelor of Computer Science and Engineering (BCSE) from Jadavpur University, Master of Computer Science and Engineering (MCSE) from Jadavpur University and PhD (Engg.) from Jadavpur University. His main area of research is Natural Language Processing. He is Professor in Computer Science and Engineering at Jadavpur University (currently on-lien). He has joined as the Director of NIT Silchar. Prior to that, he was the Head, Computer Science and Engineering Department, Jadavpur University, Dean, Faculty of Engineering and Technology, Jadavpur University, Director, Computer Aided Design Centre, Jadavpur University, Coordinator, TEQIP-II, Jadavpur University among other responsibilities.

Professor Bandyopadhyay has supervised 14 PhD students and a total of 12 PhD scholars are currently working under his supervision. He has published several research articles in reputed journals and conferences, workshops and symposiums. He has also authored two books. He has completed 4 international research and development projects – with France, Mexico, Japan as the Principal Investigator in the area of Sentiment Analysis, Question Answering, and Textual Entailment. He was the Chief Investigator of 8 National level consortium mode projects in the areas of Machine Translation – English to Indian languages and Indian language to Indian languages, cross lingual information access, development of tree bank for Indian languages among others. Currently, he is executing three international projects funded by SPARC (MHRD) with Germany, ASEAN (DST) with Indonesia and Malaysia, DST and CNRS with France. The Center for Natural Language Processing (CNLP), a research center has been established at NIT Silchar under his leadership.

Professor Bandyopadhyay has various International research collaborations and visited several countries to deliver invited talks. He is regularly organizing the workshop series “Sentiment Analysis where AI meets Psychology (SAAIP)”. He was the Program Chair of the 14th International Conference on Natural Language Processing (ICON 2017). He has started the International Conference on Big Data, Machine Learning and Applications (BigDML) in the Department of Computer Science and Engineering at NIT Silchar to be held in December, 2019.

 

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1.  Name in full (in block letters): PROF. SIVAJI BANDYOPADHYAY

2.  Address for communication (Block letters):

                       COMPUTER SCIENCE AND ENGINEERING DEPARTMENT,

                       NIT SILCHAR,

                       SILCHAR, ASSAM-788010

3. Contact Nos.:   03842-242273 / 03842-224879

Email ID: sivaji.cse.ju@gmail.com / director@nits.ac.in

4. Field / Area of Specialization: Computer Science and Engineering / Natural Language Processing

5. Number of Awards / Recognitions – 6

  • Best Teacher in Engineering, Lokmat National Education Leadership Award, 2015.

  • Selected on a Support Mission by the University Cooperation Sector, French Embassy, India for visit to France to establish research collaborations and student exchange agreements, December 2013.

  • Fellow under the infoDev Conference Scholarship Fund, World Bank to attend MT 2000, University of Exeter, UK, November 19-22, 2000.

  • University Grants Commission (UGC) Research Award for the IXth Plan Period, 1999.

  • National Scholarship on the results of Secondary Examination, 1979.

  • National Scholarship for Talented Children from Rural Areas, 1976.

 

6. Number of Ph.D. (Engg.) guided – Completed – 14, In Progress – 12

 

7. Publications Links:

 

Google Scholar Link:

https://scholar.google.co.in/citations?user=_NQqd9YAAAAJ&hl=en

 

DBLP Link:

https://dblp.org/pid/04/2897.html

 

8. Number of Books (Published & Under Publication) – 2

           i. A Practical Guide to Sentiment Analysis – Dipankar Das, Erik Cambria, Sivaji Bandyopadhyay, Feraco Antonio, Springer Publishing House, Socio Affected Computing Series, 2017.

          ii. Emerging Applications of Natural Language Processing: Concepts and New Research – Sivaji Bandyopadhyay, Sudip Kumar Naskar, Asif Ekbal, Idea Group, USA, 2012.

 

9. No. of Projects – Completed – 12, In Progress – 4

 

10. Ongoing Projects:

 

  • Deep Summarization Evaluation. PI:Dr. Partha Pakray, CO-PI:Prof. Sivaji Bandyopadhyay; Amount : Rs. 31 Lakhs (approx) Agency: DST-CNRS; Status: Ongoing
  • Healthcare ChatBot. PI:Dr. Partha Pakray; Co-PI:Prof. Sivaji Bandyopadhyay; Agency: DST-ASEAN; Status: Ongoing
  • Multimodal Machine Translation – Convergence of Multiple Modes of Input. PI:Prof. Sivaji Bandyopadhyay; CO-PI: Dr. Thoudam Doren Singh; Amount : Rs. 49.58 lacs; Agency: SPARC Status: Ongoing
  • Utilization of Agro waste for development of bio composite materials for domestic appliances. PI:Dr. Sumit Bhowmik; Co-PI:Prof. Sivaji Bandyopadhyay; Amount :Rs. 15.00 Lakh; Agency: KVIC; Status: Ongoing

 

11. List of Publications:

 

Journal:

  1. Amarnath Pathak, Riyanka Manna, Partha Pakray, Dipankar Das, Alexander Gelbukh and Sivaji Bandyopadhyay, “Scientific Text Entailment and a Textual Entailment based Framework for Cooking Domain Question Answering”, Sādhanā Springer Journal, 46, Article number: 24 (2021), Indian Academy of Sciences, Indexed in Science Citation Index – Expanded, doi: 10.1007/s12046-021-01557-9
  2. Singh, A., Singh, T.D. & Bandyopadhyay, S. An encoder-decoder based framework for hindi image caption generation. Multimed Tools Appl (2021). https://doi.org/10.1007/s11042-021-11106-5
  3. Singh, A., Singh, T.D. & Bandyopadhyay, S. Attention based video captioning framework for Hindi. Multimedia Systems (2021). https://doi.org/10.1007/s00530-021-00816-3
  4. Pankaj Dadure, Partha Pakray, and Sivaji Bandyopadhyay. “Embedding and Generalization of Formula with Context in the Retrieval of Mathematical Information”, Journal of King Saud University – Computer and Information Sciences, ISSN: 1319-1578https://doi.org/10.1016/j.jksuci.2021.05.0144
  5. Meetei, L.S., Singh, T.D., Borgohain, S.K. et al. Low resource language specific pre-processing and features for sentiment analysis task. Lang Resources & Evaluation 55, 947–969 (2021). https://doi.org/10.1007/s10579-021-09541-9
  6. Mishra, A. K., Roy, P., Bandyopadhyay, S., & Das, S. K. (2021). Breast ultrasound tumour classification: A Machine Learning—Radiomics based approach. Expert Systems, e12713. https://doi.org/10.1111/exsy.12713
  7. Khilji, A.F.U.R., Manna, R., Laskar, S.R. et al. CookingQA: Answering Questions and Recommending Recipes Based on Ingredients. Arab J Sci Eng 46, 3701–3712 (2021). https://doi.org/10.1007/s13369-020-05236-5
  8. Singh, T.D., Khilji, A.F.U.R., Divyansha et al. Predictive approaches for the UNIX command line: curating and exploiting domain knowledge in semantics deficit data. Multimed Tools Appl 80, 9209–9229 (2021). https://doi.org/10.1007/s11042-020-10109-y
  9. Mishra, A. K., Das, S. K., Roy, P., & Bandyopadhyay, S. (2020). Identifying COVID19 from chest CT images: a deep convolutional neural networks based approach. Journal of Healthcare Engineering, 2020. https://doi.org/10.1155/2020/8843664
  10. Abdullah Khilji, Riyanka Manna, Sahinur Laskar, Partha Pakray, Dipankar Das, Sivaji Bandyopadhyay, Alexander Gelbukh. “Question Classification and Answer Extraction for Developing a Cooking QA System”, Computación y Sistemas – Thematic Issue on Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez), Vol. 24, No. 2, 2020
  11. Banerjee, S., Choudhury, M., Chakma, K. et al. MSIR@FIRE: A Comprehensive Report from 2013 to 2016. SN COMPUT. SCI. 1, 55 (2020). https://doi.org/10.1007/s42979-019-0058-0
  12. Bhanja, C. C., Laskar, M. A., Laskar, R. H., & Bandyopadhyay, S. (2019). Deep neural network based two-stage Indian language identification system using glottal closure instants as anchor points. Journal of King Saud University-Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2019.07.001
  13. Mahata, S. K., Das, D., & Bandyopadhyay, S. (2019). Mtil2017: Machine translation using recurrent neural network on statistical machine translation. Journal of Intelligent Systems, 28(3), 447-453. https://doi.org/10.1515/jisys-2018-0016
  14. Patra, B. G., Das, D., & Bandyopadhyay, S. (2018). Multimodal mood classification of Hindi and Western songs. Journal of Intelligent Information Systems, 51(3), 579-596. https://doi.org/10.1007/s10844-018-0497-4
  15. Mondal, A., Cambria, E., Das, D. et al. Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis. Cogn Comput 10, 670–685 (2018). https://doi.org/10.1007/s12559-018-9567-8
  16. Banerjee, S., Naskar, S., Rosso, P., & Bandyopadhyay, S. (2018). Code mixed cross script factoid question classification-A deep learning approach. Journal of Intelligent & Fuzzy Systems, 34(5), 2959-2969. DOI: 10.3233/JIFS-169481
  17. Banerjee, S., Naskar, S. K., Rosso, P., & Bandyopadhyay, S. (2017). Named entity recognition on code-mixed cross-script social media content. Computación y Sistemas, 21(4), 681-692.
  18. Patra, B.G., Das, D. & Bandyopadhyay, S. Labeling data and developing supervised framework for hindi music mood analysis. J Intell Inf Syst 48, 633–651 (2017). https://doi.org/10.1007/s10844-016-0436-1
  19. Mukherjee, S.K., Bandyopadhyay, S. Learning topic description from clustering of trusted user roles and event models characterizing distributed provenance networks: a reinforcement learning approach. J Big Data 4, 35 (2017). https://doi.org/10.1186/s40537-017-0097-0
  20. Patra, B. G., Das, D., & Bandyopadhyay, S. (2016). Multimodal mood classification framework for Hindi songs. Computación y Sistemas, 20(3), 515-526.
  21. Chakraborty, T., Das, D., & Bandyopadhyay, S. (2014). Identifying bengali multiword expressions using semantic clustering. Lingvisticæ Investigationes, 37(1), 106-128. https://doi.org/10.1075/li.37.1.04cha
  22. Mondal, Rajendra Prasad, et al. “Functional response analysis of Anisops sardea (Hemiptera: Notonectidae) against Culex quinquefasciatus in laboratory condition.” The Indian journal of medical research 140.4 (2014): 551.
  23. Singh, Richard Laishram, et al. “A decision tree based word sense disambiguation system in Manipuri language.” Advanced Computing 5.4 (2014): 17.
  24. Nongmeikapam, K., Khangembam, D., Hemkumar, W., Khuraijam, S., & Bandyopadhyay, S. (2014). Verb based manipuri sentiment analysis. Int J Nat Lang Comput, 3(3), 113-118. 10.5121/ijnlc.2014.3311
  25. Ekbal, A., & Bandyopadhyay, S. (2014). Named entity recognition in Bengali using system combination. Lingvisticæ Investigationes, 37(1), 1-22. https://doi.org/10.1075/li.37.1.01ekb
  26. Das, D., & Bandyopadhyay, S. (2013, March). Emotion co-referencing-emotional expression, holder, and topic. In International Journal of Computational Linguistics & Chinese Language Processing, Volume 18, Number 1, March 2013.
  27. Pakray, P., Gelbukh, A., & Bandyopadhyay, S. (2013). Aplicación de la implicación textual en un sistema de la validación de respuestas automáticas. Research in Computing Science, An open access research journal on Computer science and computer engineering.
  28. Kolyal, A. K., Ekbal, A., & Bandyopadhyay, S. (2013). USING VOTING APPROACH FOR EVENT EXTRACTION AND EVENT-DCT, EVENT-TIME RELATION IDENTIFICATION. International Journal of Artificial Intelligence & Applications, 4(1), 65. 10.5121/ijaia.2013.4106
  29. Das, Dipankar, and Sivaji Bandyopadhyay. “Building Language Resources for Emotion Analysis in Bengali.” Technical Challenges and Design Issues in Bangla Language Processing. IGI Global, 2013. 346-368.DOI: 10.4018/978-1-4666-3970-6.ch016
  30. Poria, S., Gelbukh, A., Hussain, A., Howard, N., Das, D., & Bandyopadhyay, S. (2013). Enhanced SenticNet with affective labels for concept-based opinion mining. IEEE Intelligent Systems, 28(2), 31-38. DOI: 10.1109/MIS.2013.4
  31. Das, D., & Bandyopadhyay, S. (2013, March). Emotion co-referencing-emotional expression, holder, and topic. In International Journal of Computational Linguistics & Chinese Language Processing, Volume 18, Number 1, March 2013.
  32. Kundu, A., Das, D., & Bandyopadhyay, S. (2013). Scene boundary detection from movie dialogue: A genetic algorithm approach. Polibits, (47), 55-60.
  33. Bhaskar, P., Pakray, P., Gelbukh, A. F., & Bandyopadhyay, S. (2013). Entailment-based Fully Automatic Technique for Evaluation of Summaries. Res. Comput. Sci., 65, 11-23.
  34. Das, D., & Bandyopadhyay, S. (2012). Sentence-level emotion and valence tagging. Cognitive Computation, 4(4), 420-435. https://doi.org/10.1007/978-981-15-6318-8_12
  35. Das, D., & Bandyopadhyay, S. (2012). Tracking Emotions of Bloggers: A Case Study for Bengali. Polibits, (45), 53-59. On-line ISSN 1870-9044
  36. Kumar Kolya, A., Ekbal, A., & Bandyopadhyay, S. (2012). A hybrid approach for event extraction. Polibits, (46), 55-59. On-line ISSN 1870-9044
  37. Nongmeikapam, K., Nonglenjaoba, L., Nirmal, Y., & Bandhyopadhyay, S. (2012). REDUPLICATED MWE (RMWE) HELPS IN IMPROVING THE CRF BASED MANIPURI POS TAGGER. International Journal of Information Technology Convergence and Services, 2(1), 45.
  38. Bhaskar, P., & Bandyopadhyay, S. (2012). Cross lingual query dependent snippet generation. International Journal of Computer Science and Information Technologies (IJCSIT), ISSN, 0975-9646.
  39. Kishorjit, N., & Sivaji, B. (2012). A Transliteration of CRF Based Manipuri POS Tagging. In the Proceedings of 2nd International Conference on Communication, Computing & Security (ICCCS-2012), Elsevier Ltd (Vol. 201, No. 2). https://doi.org/10.1016/j.protcy.2012.10.070
  40. Bhaskar, P., & Bandyopadhyay, S. (2012). Answer extraction of comparative and evaluative question in tourism domain. International Journal of Computer Science and Information Technologies (IJCSIT), ISSN, 0975-9646.
  41. Pakray, Partha, Utsab Barman, Sivaji Bandyopadhyay, and Alexander Gelbukh. “Semantic answer validation using universal networking language.” International Journal of Computer Science and Information Technologies 3, no. 4 (2012): 4927-4932.
  42. Das, D., & Bandyopadhyay, S. (2011). Document level emotion tagging: machine learning and resource based approach. Computación y Sistemas, 15(2), 221-234. On-line ISSN 2007-9737
  43. Pakray, P., Poria, S., Bandyopadhyay, S., & Gelbukh, A. (2011). Semantic textual entailment recognition using UNL. Polibits, (43), 23-27. On-line ISSN 1870-9044
  44. Chakraborty, T., & Bandyopadhyay, S. (2011). Inference of fine-grained attributes of bengali corpus for stylometry detection. Polibits, (44), 79-83. On-line ISSN 1870-9044
  45. Ekbal, A., & Bandyopadhyay, S. (2011). Named entity recognition in Bengali and Hindi using support vector machine. Lingvisticæ Investigationes, 34(1), 35-67.https://doi.org/10.1075/li.34.1.02ekb
  46. Das, A., & Bandyopadhyay, S. (2011). Syntactic Sentence Fusion Techniques for Bengali. International Journal of Computer Science and Information Technologies, 2(1), 494-503.
  47. Chakraborty, T., & Bandyopadhyay, S. (2010, November). Authorship Identification Using Stylometry Analysis: A CRF Based Approach. In Proceedings of IEEE Cascom Postgraduate Student Paper Conference, Jadavpur University, Kolkata (pp. 66-69).
  48. Ekbal, A., & Bandyopadhyay, S. (2010). Named entity recognition using support vector machine: A language independent approach. International Journal of Electrical, Computer, and Systems Engineering, 4(2), 155-170.
  49. Das, A., & Bandyopadhyay, S. (2010). Phrase-level polarity identification for Bangla. Int. J. Comput. Linguist. Appl.(IJCLA), 1(1-2), 169-182.
  50. Singh, T. D., & Bandyopadhyay, S. (2010). Manipuri-english example based machine translation system,”. International Journal of Computational Linguistics and Applications (IJCLA), ISSN, 0976-0962.
  51. Ekbal, A., & Bandyopadhyay, S. (2010). Named entity recognition using appropriate unlabeled data, post-processing and voting. Informatica, 34(1).
  52. Das, D., & Bandyopadhyay, S. (2010). Sentence level emotion tagging on blog and news corpora. Journal of intelligent systems, 19(2), 145-162. https://doi.org/10.1515/JISYS.2010.19.2.145
  53. Singh, T. D., & Bandyopadhyay, S. (2010). Semi-Automatic Parallel Corpora Extraction from Comparable News Corpora. Polibits, (41), 11-17.
  54. Ekbal, A., & Bandyopadhyay, S. (2009). A conditional random field approach for named entity recognition in Bengali and Hindi. Linguistic Issues in Language Technology, 2(1), 1-44.
  55. Hasanuzzaman, M., Ekbal, A., & Bandyopadhyay, S. (2009). Maximum entropy approach for named entity recognition in bengali and hindi. International Journal of Recent Trends in Engineering, 1(1), 408.
  56. Ekbal, A., & Bandyopadhyay, S. (2009). Named Entity Recognition in Bengali. Northern European Journal of Language Technology, 1, 26-58. https://doi.org/10.3384/nejlt.2000-1533.091226
  57. Ekbal, A., & Bandyopadhyay, S. (2009). A multiengine NER system with context pattern learning and post-processing improves system performance. International Journal of Computer Processing Of Languages, 22(02n03), 171-204. https://doi.org/10.1142/S1793840609002068
  58. Ekbal, A., & Bandyopadhyay, S. (2008). Named entity recognition in indian languages using maximum entropy approach. International Journal of Computer Processing Of Languages, 21(03), 205-237. https://doi.org/10.1142/S1793840608001913
  59. Ekbal, A., Bandyopadhyay, S. A web-based Bengali news corpus for named entity recognition. Lang Resources & Evaluation 42, 173–182 (2008). https://doi.org/10.1007/s10579-008-9064-x
  60. Ekbal, A., & Bandyopadhyay, S. (2008). Web-based Bengali news corpus for lexicon development and POS tagging. Polibits, (37), 21-30.
  61. Ekbal, A., Haque, R., & Bandyopadhyay, S. (2008). Maximum entropy based bengali part of speech tagging. A. Gelbukh (Ed.), Advances in Natural Language Processing and Applications, Research in Computing Science (RCS) Journal, 33, 67-78.
  62. Bandyopadhyay, S., & Ekbal, A. (2007). HMM based POS Tagger and Rule-based Chunker for Bengali. In Advances In Pattern Recognition (pp. 384-390). https://doi.org/10.1142/9789812772381_0065
  63. Ekbal, A., Naskar, S. K., & Bandyopadhyay, S. (2007). Named entity recognition and transliteration in Bengali. Lingvisticae Investigationes, 30(1), 95-114.  https://doi.org/10.1075/li.30.1.07ekb
  64. Ekbal, A., & Bandyopadhyay, S. (2007). Pattern Based Bootstrapping Method for Named Entity Recognition. In Advances In Pattern Recognition (pp. 349-355). https://doi.org/10.1142/9789812772381_0059
  65. Ekbal, A., Naskar, S. K., & Bandyopadhyay, S. (2007). Named entity transliteration. International Journal of Computer Processing of Oriental Languages, 20(04), 289-310. https://doi.org/10.1142/S021942790700169X
  66. Naskar, S., & Bandyopadhyay, S. (2005). Use of machine translation in India: Current status. AAMT Journal, 25-31. https://doi.org/10.1.1.579.9769

Conferences/Workshops:

  1. Laskar, S. R., Darsh, A. F. U. R. K., Pakray, P., & Bandyopadhyay, S. (2021, August). EnKhCorp1. 0: An English–Khasi Corpus. In Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021) (pp. 89-95).
  2. Laskar, S. R., Khilji, A. F. U. R., Kaushik, D., Pakray, P., & Bandyopadhyay, S. (2021, August). Improved English to Hindi Multimodal Neural Machine Translation. In Proceedings of the 8th Workshop on Asian Translation (WAT2021) (pp. 155-160).
  3. Laskar, S. R., Pakray, P., & Bandyopadhyay, S. (2021, May). Neural Machine Translation for Low Resource Assamese–English. In Proceedings of the International Conference on Computing and Communication Systems: I3CS 2020, NEHU, Shillong, India (Vol. 170, p. 35). Springer Nature.
  4. Dadure P., Pakray P., Bandyopadhyay S. (2021) Efficient Assessment of Formula Representation in Embedded Vector. In: Maji A.K., Saha G., Das S., Basu S., Tavares J.M.R.S. (eds) Proceedings of the International Conference on Computing and Communication Systems. Lecture Notes in Networks and Systems, vol 170. Springer, Singapore. https://doi.org/10.1007/978-981-33-4084-8_3
  5. Mahata, S., Das, D., & Bandyopadhyay, S. (2021, April). Sentiment Classification of Code-Mixed Tweets using Bi-Directional RNN and Language Tags. In Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages (pp. 28-35).
  6. Dadure, P., Pakray, P., & Bandyopadhyay, S. (2021). BERT-Based Embedding Model for Formula Retrieval.
  7. Mishra A.K., Roy P., Bandyopadhyay S. (2021) Binary Particle Swarm Optimization Based Feature Selection (BPSO-FS) for Improving Breast Cancer Prediction. In: Bansal P., Tushir M., Balas V., Srivastava R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_35
  8. Mahata S.K., Chandra A., Das D., Bandyopadhyay S. (2021) Preparation of Sentiment tagged Parallel Corpus and Testing Its Effect on Machine Translation. In: Patgiri R., Bandyopadhyay S., Balas V.E. (eds) Proceedings of International Conference on Big Data, Machine Learning and Applications. Lecture Notes in Networks and Systems, vol 180. Springer, Singapore. https://doi.org/10.1007/978-981-33-4788-5_11
  9. Singh, A., Meetei, L. S., Singh, T. D., & Bandyopadhyay, S. (2021). Generation and evaluation of hindi image captions of visual genome. In Proceedings of the International Conference on Computing and Communication Systems: I3CS 2020, NEHU, Shillong, India (pp. 65-73). Springer Singapore.
  10. Sahinur Rahman Laskar, Partha Pakray and Sivaji Bandyopadhyay, “Neural Machine Translation: Assamese↔Bengali”, in the International Conference on Modeling, Simulation and Optimization (CoMSO 2020), Springer, National Institute of Technology Silchar, August 3-5, 2020, pp 571-579, vol 206, DOI: https://doi.org/10.1007/978-981-15-9829-6_4
  11. Mahata, S. K., Dutta, S., Das, D., & Bandyopadhyay, S. (2020, December). Performance Gain in Low Resource MT with Transfer Learning: An Analysis concerning Language Families. In Forum for Information Retrieval Evaluation (pp. 58-61).
  12. Mahata, S., Das, D., & Bandyopadhyay, S. (2020, December). JUNLP@ ICON2020: Low Resourced Machine Translation for Indic Languages. In Proceedings of the 17th International Conference on Natural Language Processing (ICON): Adap-MT 2020 Shared Task (pp. 1-5).
  13. Meetei, L. S., Singh, T. D., Bandyopadhyay, S., Vela, M., & van Genabith, J. (2020, December). English to Manipuri and Mizo Post-Editing Effort and its Impact on Low Resource Machine Translation. In Proceedings of the 17th International Conference on Natural Language Processing (ICON) (pp. 50-59).
  14. Laskar, S. R., Khilji, A. F. U. R., Pakray, P., & Bandyopadhyay, S. (2020, December). EnAsCorp1. 0: English-Assamese Corpus. In Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages (pp. 62-68).
  15. Laskar, S. R., Khilji, A. F. U. R., Pakray, P., & Bandyopadhyay, S. (2020, December). Zero-shot neural machine translation: Russian-Hindi@ loresmt 2020. In Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages (pp. 38-42).
  16. Laskar, S. R., Khilji, A. F. U. R., Pakray, P., & Bandyopadhyay, S. (2020, December). Multimodal Neural Machine Translation for English to Hindi. In Proceedings of the 7th Workshop on Asian Translation (pp. 109-113).
  17. Laskar, S. R., Khilji, A. F. U. R., Pakray, P., & Bandyopadhyay, S. (2020, November). Hindi-marathi cross lingual model. In Proceedings of the Fifth Conference on Machine Translation (pp. 396-401).
  18. Singh, S. M., Singh, T. D., & Bandyopadhyay, S. (2020, November). The NITS-CNLP System for the Unsupervised MT Task at WMT 2020. In Proceedings of the Fifth Conference on Machine Translation (pp. 1139-1143).
  19. Mahata, S. K., Das, D., & Bandyopadhyay, S. (2020). JUNLP@ Dravidian-CodeMix-FIRE2020: Sentiment Classification of Code-Mixed Tweets using Bi-Directional RNN and Language Tags. arXiv preprint arXiv:2010.10111.
  20. Das D., Biswas S.K., Bandyopadhyay S., Sarkar S. (2020) Early Detection of Diabetic Retinopathy Using Machine Learning Techniques: A Survey on Recent Trends and Techniques. In: Mallick P.K., Meher P., Majumder A., Das S.K. (eds) Electronic Systems and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 686. Springer, Singapore. https://doi.org/10.1007/978-981-15-7031-5_64
  21. D. Das, S. K. Biswas, S. Bandyopadhyay and R. H. Laskar, “Deep Learning Techniques for Early Detection of Diabetic Retinopathy: Recent Developments and Techniques,” 2020 5th International Conference on Computing, Communication and Security (ICCCS), 2020, pp. 1-7, doi: 10.1109/ICCCS49678.2020.9276781.
  22. Shome N., Laskar R.H., Kashyap R., Bandyopadhyay S. (2020) A Robust Technique for End Point Detection Under Practical Environment. In: Bhattacharjee A., Borgohain S., Soni B., Verma G., Gao XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1241. Springer, Singapore. https://doi.org/10.1007/978-981-15-6318-8_12
  23. Shome, N., Laskar, R. H., Kashyap, R., & Bandyopadhyay, S. (2020, July). A Robust Technique for End Point Detection Under Practical Environment. In International Conference on Machine Learning, Image Processing, Network Security and Data Sciences (pp. 131-144). Springer, Singapore.
  24. Khilji, A. F. U. R., Laskar, S. R., Pakray, P., Kadir, R. A., Lydia, M. S., & Bandyopadhyay, S. (2020, July). Healfavor: Dataset and a prototype system for healthcare chatbot. In 2020 International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA) (pp. 1-4). IEEE.
  25. Boruah, A. N., Biswas, S. K., Bandyopadhyay, S., & Sarkar, S. (2020, July). Expert System to Manage Parkinson Disease by Identifying Risk Factors: TD-Rules-PD. In 2020 International Conference on Computational Performance Evaluation (ComPE) (pp. 001-006). IEEE.
  26. Abdullah Faiz Ur Rahman Khilji , Sahinur Rahman Laskar, Partha Pakray and Sivaji Bandyopadhyay, “Urdu Fake News Detection using Generalized Autoregressors”, Working Notes – The 2020 Fake News Detection in the Urdu Language Task, Forum for Information Retrieval Evaluation 2020, Dec 16-20, 2020, Hyderabad, India
  27. Meetei L.S., Das R., Singh T.D., Bandyopadhyay S. (2020) Automatic Extraction of Locations from News Articles Using Domain Knowledge. In: Patgiri R., Bandyopadhyay S., Borah M.D., Thounaojam D.M. (eds) Big Data, Machine Learning, and Applications. BigDML 2019. Communications in Computer and Information Science, vol 1317. Springer, Cham. https://doi.org/10.1007/978-3-030-62625-9_4
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  30. Pankaj Dadure, Partha Pakray and Sivaji Bandyopadhyay, “Preliminary Investigation on Causality Information Retrieval”, Working Notes – Causality-driven Ad hoc Information Retrieval (CAIR), Forum for Information Retrieval Evaluation 2020, Dec 16-20, 2020, Hyderabad, India CEUR Workshop Proceedings
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  33. Laskar, S. R., Dutta, A., Pakray, P., & Bandyopadhyay, S. (2019, December). Neural machine translation: English to hindi. In 2019 IEEE conference on information and communication technology (pp. 1-6). IEEE.
  34. Laskar, S. R., Singh, R. P., Pakray, P., & Bandyopadhyay, S. (2019, November). English to Hindi multi-modal neural machine translation and Hindi image captioning. In Proceedings of the 6th Workshop on Asian Translation (pp. 62-67).
  35. Meetei, L. S., Singh, T. D., & Bandyopadhyay, S. (2019, November). WAT2019: English-Hindi translation on Hindi visual genome dataset. In Proceedings of the 6th Workshop on Asian Translation (pp. 181-188).
  36. Mishra A.K., Roy P., Bandyopadhyay S. (2020) Genetic Algorithm Based Selection of Appropriate Biomarkers for Improved Breast Cancer Prediction. In: Bi Y., Bhatia R., Kapoor S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_54
  37. Sahinur Rahman Laskar, Partha Pakray and Sivaji Bandyopadhyay “Neural Machine Translation: Hindi-Nepali”, in the Proceedings of the Fourth Conference on Machine Translation (WMT), Publisher: Association for Computational Linguistics, doi 10.18653/v1/W19-5427, Volume 2: Shared Task Papers, pages 900–905, Florence, Italy, August 1-2, 2019.
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  39. Mondal, A., Das, D., Cambria, E., & Bandyopadhyay, S. (2018, January). WME 3.0: an enhanced and validated lexicon of medical concepts. In Proceedings of the 9th Global WordNet Conference (pp. 10-16).
  40. Mahata, S. K., Garain, A., Rayala, A., Das, D., & Bandyopadhyay, S. JUMT at WMT2019 News Translation Task: A Hybrid approach to Machine Translation for Lithuanian to English. http://dx.doi.org/10.18653/v1/W19-5328
  41. Mahata, S. K., Das, D., & Bandyopadhyay, S. JUCBNMT at WMT2018 News Translation Task: Character Based Neural Machine Translation of Finnish to English.
  42. Sarkar, A., Dasgupta, S., Naskar, S. K., & Bandyopadhyay, S. (2018, April). Says who? deep learning models for joint speech recognition, segmentation and diarization. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 5229-5233). IEEE.
  43. Patra B.G., Mazumdar S., Das D., Rosso P., Bandyopadhyay S. (2018) A Multilevel Approach to Sentiment Analysis of Figurative Language in Twitter. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2016. Lecture Notes in Computer Science, vol 9624. Springer, Cham. https://doi.org/10.1007/978-3-319-75487-1_22
  44. Patra, B. G., Das, D., & Bandyopadhyay, S. (2017, December). Retrieving similar lyrics for music recommendation system. In Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017) (pp. 290-297).
  45. Bandyopadhyay, S. (2017, December). Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017). In Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017).
  46. Cambria, E., Das, D., Bandyopadhyay, S., & Feraco, A. (Eds.). (2017). A practical guide to sentiment analysis (pp. 1-196). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-55394-8
  47. Mondal, A., Cambria, E., Feraco, A., Das, D., & Bandyopadhyay, S. (2017). Auto-categorization of medical concepts and contexts. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-7). IEEE. https://doi.org/10.1109/SSCI.2017.8285253
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  49. Cambria E., Das D., Bandyopadhyay S., Feraco A. (2017) Affective Computing and Sentiment Analysis. In: Cambria E., Das D., Bandyopadhyay S., Feraco A. (eds) A Practical Guide to Sentiment Analysis. Socio-Affective Computing, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-55394-8_1
  50. Mukherjee, S.K., Bandyopadhyay, S. Learning topic description from clustering of trusted user roles and event models characterizing distributed provenance networks: a reinforcement learning approach. J Big Data 4, 35 (2017). https://doi.org/10.1186/s40537-017-0097-0
  51. Mahata, S. K., Das, D., & Bandyopadhyay, S. (2017). BUCC2017: A Hybrid Approach for Identifying Parallel Sentences in Comparable Corpora. ACL 2017, 56.
  52. Saikh T., Naskar S.K., Ekbal A., Bandyopadhyay S. (2018) Textual Entailment Using Machine Translation Evaluation Metrics. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2017. Lecture Notes in Computer Science, vol 10761. Springer, Cham. https://doi.org/10.1007/978-3-319-77113-7_25
  53. Mondal, A., Cambria, E., Das, D., & Bandyopadhyay, S. (2017, May). Mediconceptnet: an affinity score based medical concept network. In The Thirtieth International Flairs Conference.
  54. Mondal, A., Das, D., & Bandyopadhyay, S. (2017, December). Relationship extraction based on category of medical concepts from lexical contexts. In Proceedings of the 14th international conference on natural language processing (ICON-2017) (pp. 212-219).
  55. Mondal, A., Cambria, E., Das, D., & Bandyopadhyay, S. (2017). Employing sentiment-based affinity and gravity scores to identify relations of medical concepts. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-7). IEEE.
  56. Bandyopadhyay, S. (2017, December). Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017). In Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017).
  57. Patra B.G., Mazumdar S., Das D., Rosso P., Bandyopadhyay S. (2018) A Multilevel Approach to Sentiment Analysis of Figurative Language in Twitter. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2016. Lecture Notes in Computer Science, vol 9624. Springer, Cham. https://doi.org/10.1007/978-3-319-75487-1_22
  58. Patra, B. G., Das, D., & Bandyopadhyay, S. (2016, December). Multimodal mood classification-a case study of differences in hindi and western songs. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers (pp. 1980-1989).
  59. Banerjee, S., Naskar, S. K., Rosso, P., & Bandyopadhyay, S. (2016, March). The First Cross-Script Code-Mixed Question Answering Corpus. In MultiLingMine@ ECIR (pp. 56-65).
  60. Dasgupta, S., Kumar, A., Das, D., Naskar, S. K., & Bandyopadhyay, S. (2016, December). Word Embeddings for Information Extraction from Tweets. In FIRE (Working Notes) (pp. 71-73).
  61. Banerjee S. et al. (2018) Overview of the Mixed Script Information Retrieval (MSIR) at FIRE-2016. In: Majumder P., Mitra M., Mehta P., Sankhavara J. (eds) Text Processing. FIRE 2016. Lecture Notes in Computer Science, vol 10478. Springer, Cham. https://doi.org/10.1007/978-3-319-73606-8_3
  62. Saikh, T., Naskar, S. K., & Bandyopadhyay, S. JU_NLP@ DPIL-FIRE2016: Paraphrase Detection in Indian Languages-A Machine Learning Approach.
  63. Nongmeikapam, K., & Bandyopadhyay, S. (2016, December). Genetic Algorithm (GA) Implementation for Feature Selection in Manipuri POS Tagging. In Proceedings of the 13th International Conference on Natural Language Processing (pp. 267-274).
  64. Mondal, A., Satapathy, R., Das, D., & Bandyopadhyay, S. (2016, January). A hybrid approach based sentiment extraction from medical context. In SAAIP@ IJCAI.
  65. Mahapatra, J., Naskar, S. K., & Bandyopadhyay, S. (2016). Statistical natural language generation from tabular non-textual data. In Proceedings of the 9th International Natural Language Generation conference (pp. 143-152).
  66. Saikh T., Das D., Bandyopadhayay S. (2017) Identifying and Pruning Features for Classifying Translated and Post-edited Gaze Durations. In: Prasath R., Gelbukh A. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2016. Lecture Notes in Computer Science, vol 10089. Springer, Cham. https://doi.org/10.1007/978-3-319-58130-9_12
  67. Patra, B. G., Das, D., & Bandyopadhyay, S. (2016, June). JU_NLP at semeval-2016 task 6: Detecting stance in Tweets using support vector machines. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) (pp. 440-444).
  68. Mukherjee, N., Patra, B. G., Das, D., & Bandyopadhyay, S. (2016, June). Ju_nlp at semeval-2016 task 11: Identifying complex words in a sentence. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) (pp. 986-990).
  69. Pahari, K., Kuila, A., Pal, S., Naskar, S. K., Bandyopadhyay, S., & van Genabith, J. (2016, August). JU-USAAR: A Domain Adaptive MT System. In Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers (pp. 442-448).
  70. Mondal, A., Das, D., Cambria, E., & Bandyopadhyay, S. (2016). Wme: Sense, polarity and affinity based concept resource for medical events. In Proceedings of the 8th Global WordNet Conference (GWC) (pp. 243-248).
  71. Nayak, T., Pal, S., Naskar, S. K., Bandyopadhyay, S., & van Genabith, J. (2016, May). Beyond translation memories: generating translation suggestions based on parsing and POS tagging. In Proceedings of the 2nd Workshop on Natural Language Processing for Translation Memories (NLP4TM-2016), Portoroz, Slovenia (Vol. 28).
  72. Saikh, T., Bangalore, S., Carl, M., & Bandyopadhyay, S. (2015, March). Predicting source gaze fixation duration: A machine learning approach. In 2015 International Conference on Cognitive Computing and Information Processing (CCIP) (pp. 1-6). IEEE. https://doi.org/10.1109/CCIP.2015.7100708
  73. Patra, B. G., Das, D., & Bandyopadhyay, S. (2015). Music emotion recognition system. In Proceedings of the international symposium frontiers of research speech and music (FRSM-2015) (pp. 114-119).
  74. Patra B.G., Ghosh N., Das D., Bandyopadhyay S. (2015) Identifying Temporal Information and Tracking Sentiment in Cancer Patients’ Interviews. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science, vol 9042. Springer, Cham. https://doi.org/10.1007/978-3-319-18117-2_14
  75. Saikh T., Naskar S.K., Giri C., Bandyopadhyay S. (2015) Textual Entailment Using Different Similarity Metrics. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science, vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_37
  76. Sequiera, R., Choudhury, M., Gupta, P., Rosso, P., Kumar, S., Banerjee, S., … & Chakma, K. (2015, December). Overview of FIRE-2015 Shared Task on Mixed Script Information Retrieval. In FIRE workshops (Vol. 1587, pp. 19-25).
  77. Mandal, S., Banerjee, S., Naskar, S. K., Rosso, P., & Bandyopadhyay, S. (2015). Adaptive Voting in Multiple Classifier Systems for Word Level Language Identification. In FIRE workshops (pp. 47-50).
  78. Choudhury, S., Banerjee, S., Naskar, S. K., Rosso, P., & Bandyopadhyay, S. (2015). Entity Extraction from Social Media using Machine Learning Approaches. In FIRE Workshops (pp. 103-106).
  79. Patra, B. G., Debbarma, N., Das, D., & Bandyopadhyay, S. (2015, October). Named Entity Recognizer for less resourced language Kokborok. In 2015 International Conference on Asian Language Processing (IALP) (pp. 164-168). IEEE.
  80. Mondal, A., Chaturvedi, I., Das, D., Bajpai, R., & Bandyopadhyay, S. (2015, November). Lexical resource for medical events: A polarity based approach. In 2015 IEEE International Conference on Data Mining Workshop (ICDMW) (pp. 1302-1309). IEEE.
  81. Patra, B. G., Das, D., & Bandyopadhyay, S. (2015, December). Mood classification of hindi songs based on lyrics. In Proceedings of the 12th international conference on natural language processing (pp. 261-267).
  82. Patra, B. G., Maitra, P., Das, D., & Bandyopadhyay, S. (2015, September). MediaEval 2015: Music Emotion Recognition based on Feed-Forward Neural Network. In MediaEval.
  83. Mukherjee, S. K., & Bandyopadhyay, S. (2015, July). Clustering to determine predictive model for news reports analysis and econometric modeling. In 2015 IEEE 2nd International Conference on Recent trends in information systems (ReTIS) (pp. 302-309). IEEE.
  84. Mohan, D. C., Das, D., & Bandyopadhyay, S. (2015, July). Emotion argumentation. In 2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS) (pp. 331-336). IEEE. DOI: 10.1109/ReTIS.2015.7232900
  85. Lohar P., Bhaskar P., Pal S., Bandyopadhyay S. (2014) Cross Lingual Snippet Generation Using Snippet Translation System. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54903-8_28
  86. Banerjee, S., Kuila, A., Roy, A., Naskar, S. K., Rosso, P., & Bandyopadhyay, S. (2014, December). A hybrid approach for transliterated word-level language identification: Crf with post-processing heuristics. In Proceedings of the Forum for Information Retrieval Evaluation (pp. 54-59).
  87. Pal, S., Patra, B. G., Das, D., Naskar, S. K., Bandyopadhyay, S., & van Genabith, J. (2014, December). How sentiment analysis can help machine translation. In Proceedings of the 11th International Conference on Natural Language Processing (pp. 89-94).
  88. Nongmeikapam, K., Singh, T. I., Chanu, N. M., & Bandyopadhyay, S. (2014, December). Manipuri Chunking: An Incremental Model with POS and RMWE. In Proceedings of the 11th International Conference on Natural Language Processing (pp. 277-286).
  89. Pal, S., Naskar, S. K., & Bandyopadhyay, S. (2014, May). Word Alignment-Based Reordering of Source Chunks in PB-SMT. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14).
  90. Patra, B. G., Mukherjee, N., Das, A., Mandal, S., Das, D., & Bandyopadhyay, S. (2014, November). Identifying aspects and analyzing their sentiments from reviews. In 2014 13th Mexican International Conference on Artificial Intelligence (pp. 9-15). IEEE. DOI: 10.1109/MICAI.2014.8
  91. Patra, B. G., Soumik, M., Das, D., & Sivaji, B. (2014). Ju_cse: A conditional random field (crf) based approach to aspect based sentiment analysis.
  92. Banerjee S., Lohar P., Naskar S.K., Bandyopadhyay S. (2014) The First Resource for Bengali Question Answering Research. In: Przepiórkowski A., Ogrodniczuk M. (eds) Advances in Natural Language Processing. NLP 2014. Lecture Notes in Computer Science, vol 8686. Springer, Cham. https://doi.org/10.1007/978-3-319-10888-9_30
  93. Banerjee S., Naskar S.K., Bandyopadhyay S. (2014) Bengali Named Entity Recognition Using Margin Infused Relaxed Algorithm. In: Sojka P., Horák A., Kopeček I., Pala K. (eds) Text, Speech and Dialogue. TSD 2014. Lecture Notes in Computer Science, vol 8655. Springer, Cham. https://doi.org/10.1007/978-3-319-10816-2_16
  94. Banerjee S., Naskar S.K., Bandyopadhyay S. (2014) BFQA: A Bengali Factoid Question Answering System. In: Sojka P., Horák A., Kopeček I., Pala K. (eds) Text, Speech and Dialogue. TSD 2014. Lecture Notes in Computer Science, vol 8655. Springer, Cham. https://doi.org/10.1007/978-3-319-10816-2_27
  95. Das, D., & Bandyopadhyay, S. (2014). Emotion analysis on social media: natural language processing approaches and applications. In Online Collective Action (pp. 19-37). Springer, Vienna. https://doi.org/10.1007/978-3-7091-1340-0_2
  96. Kolya, A. K., Pal, S., Ekbal, A., & Bandyopadhyay, S. (2013, October). Event and Event Actor Alignment in Phrase Based Statistical Machine Translation. In Proceedings of the 11th Workshop on Asian Language Resources (pp. 36-44).
  97. Patra, B. G., Das, D., & Bandyopadhyay, S. (2013, October). Automatic music mood classification of Hindi songs. In Proceedings of the 3rd Workshop on Sentiment Analysis where AI meets Psychology (pp. 24-28).
  98. Sarkar, S., & Bandyopadhyay, S. (2013, October). On Application of Conditional Random Field in Stemming of Bengali Natural Language Text. In Proceedings of the 4th Workshop on South and Southeast Asian Natural Language Processing (pp. 34-42).
  99. Gupta, R., & Bandyopadhyay, S. (2013, March). Testing the Effectiveness of Named Entities in Aligning Comparable English-Bengali Document Pair. In International Conference on Intelligent Interactive Technologies and Multimedia (pp. 102-110). Springer, Berlin, Heidelberg.https://doi.org/10.1007/978-3-642-37463-0_9
  100. Patra, B. G., Banerjee, S., Das, D., & Bandyopadhyay, S. (2013). Feeling may separate two authors: Incorporating sentiment in authorship identification task. Small, 26, 72.
  101. Dagan, I., Roth, D., Sammons, M., & Zanzotto, F. M. (2013). Recognizing textual entailment: Models and applications. Synthesis Lectures on Human Language Technologies, 6(4), 1-220.
  102. Bhaskar, P., Banerjee, S., & Bandyopadhyay, S. (2013). Tweet Contextualization (Answering Tweet Question)-the Role of Multi-document Summarization. In CLEF (Working Notes).
  103. Banerjee, S., & Bandyopadhyay, S. (2013). Ensemble approach for fine-grained question classification in bengali. In 27th Pacific Asia Conference on Language, Information, and Computation (pp. 75-84).
  104. Pal, Santanu, Mahammed Hasanuzzaman, Sudip Kumar Naskar, and Sivaji Bandyopadhyay. “Impact of linguistically motivated shallow phrases in pb-smt.” ICON (2013).
  105. Gupta, R., Pal, S., & Bandyopadhyay, S. (2013, August). Improving mt system using extracted parallel fragments of text from comparable corpora. In Proceedings of the Sixth Workshop on Building and Using Comparable Corpora (pp. 69-76).
  106. Banerjee, S., Bhaskar, P., Pakray, P., Bandyopadhyay, S., & Gelbukh, A. F. (2013, January). Multiple Choice Question (MCQ) Answering System for Entrance Examination. In CLEF (Working Notes).
  107. Bhaskar, P., Banerjee, S., & Bandyopadhyay, S. (2013). Tweet Contextualization (Answering Tweet Question)-the Role of Multi-document Summarization. In CLEF (Working Notes).
  108. Bhaskar, P., Banerjee, S., Pakray, P., Banerjee, S., Bandyopadhyay, S., & Gelbukh, A. (2013, January). A hybrid question answering system for Multiple Choice Question (MCQ). In QA4MRE at Conference and Labs of the Evaluation Forum. sn.
  109. Patra, B. G., Banerjee, S., Das, D., Saikh, T., & Bandyopadhyay, S. (2013). Automatic Author Profiling Based on Linguistic and Stylistic Features Notebook for PAN at CLEF 2013.
  110. Pal, S., Naskar, S. K., & Bandyopadhyay, S. (2013, August). A hybrid word alignment model for phrase-based statistical machine translation. In Proceedings of the Second Workshop on Hybrid Approaches to Translation (pp. 94-101).
  111. Patra, B. G., Takamura, H., Das, D., Okumura, M., & Bandyopadhyay, S. (2013, October). Construction of emotional lexicon using potts model. In Proceedings of the Sixth International Joint Conference on Natural Language Processing (pp. 674-679).
  112. Banerjee, S., & Bandyopadhyay, S. (2013, October). An empirical study of combing multiple models in bengali question classification. In Proceedings of the Sixth International Joint Conference on Natural Language Processing (pp. 892-896).
  113. Poria S., Gelbukh A., Hussain A., Bandyopadhyay S., Howard N. (2013) Music Genre Classification: A Semi-supervised Approach. In: Carrasco-Ochoa J.A., Martínez-Trinidad J.F., Rodríguez J.S., di Baja G.S. (eds) Pattern Recognition. MCPR 2013. Lecture Notes in Computer Science, vol 7914. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38989-4_26
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  115. Das, A., Burman, U., Balamurali, A. R., & Bandyopadhyay, S. (2013). NER from Tweets: SRI-JU System@ MSM 2013. Making Sense of Microposts (# MSM2013).
  116. Pal, S., Naskar, S. K., & Bandyopadhyay, S. (2013). MWE alignment in phrase based statistical machine translation. The XIV Machine Translation Summit, 61-68.
  117. Pakray, P., Bandyopadhyay, S., & Gelbukh, A. F. (2013, June). Binary-class and Multi-class based Textual Entailment System. In NTCIR.
  118. Kolya, A. K., Kundu, A., Gupta, R., Ekbal, A., & Bandyopadhyay, S. (2013, June). JU_CSE: A CRF based approach to annotation of temporal expression, event and temporal relations. In Second Joint Conference on Lexical and Computational Semantics (* SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (pp. 64-72).
  119. Das D., Bandyopadhyay S. (2013) Holder and Topic Based Analysis of Emotions on Blog Texts: A Case Study for Bengali. In: Özyer T., Erdem Z., Rokne J., Khoury S. (eds) Mining Social Networks and Security Informatics. Lecture Notes in Social Networks. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6359-3_7
  120. Bhaskar, P., Ghosh, A., Pal, S., & Bandyopadhyay, S. (2012, June). Detection and correction of preposition and determiner errors in English: HOO 2012. In Proceedings of the Seventh Workshop on Building Educational Applications Using NLP (pp. 201-207).
  121. Bhaskar, P., Pal, B. C., & Bandyopadhyay, S. (2012, October). Comparative & Evaluative QA system in tourism domain. In Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology (pp. 458-465). https://doi.org/10.1145/2393216.2393293
  122. Nongmeikapam K., Sharma A.U., Devi L.M., Keisam N., Singh K.D., Bandyaopadhyay S. (2012) Will the Identification of Reduplicated Multiword Expression (RMWE) Improve the Performance of SVM Based Manipuri POS Tagging?. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_10
  123. Kolya A.K., Das D., Ekbal A., Bandyaopadhyay S. (2012) Roles of Event Actors and Sentiment Holders in Identifying Event-Sentiment Association. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_42
  124. Das A., Bandyaopadhyay S., Gambäck B. (2012) The 5W Structure for Sentiment Summarization-Visualization-Tracking. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_44
  125. Bhaskar P., Bandyopadhyay S. (2012) Language Independent Query Focused Snippet Generation. In: Catarci T., Forner P., Hiemstra D., Peñas A., Santucci G. (eds) Information Access Evaluation. Multilinguality, Multimodality, and Visual Analytics. CLEF 2012. Lecture Notes in Computer Science, vol 7488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33247-0_16
  126. Bhaskar, P., Banerjee, S., & Bandyopadhyay, S. (2012, September). A hybrid tweet contextualization system using IR and summarization.  (p. 164).
  127. Bhaskar, P., Pakray, P., Banerjee, S., Banerjee, S., Bandyopadhyay, S., & Gelbukh, A. F. (2012, September). Question Answering System for QA4MRE@ CLEF 2012. In CLEF (Online Working Notes/Labs/Workshop).
  128. Pakray, P., Bhaskar, P., Banerjee, S., Bandyopadhyay, S., & Gelbukh, A. F. (2012, January). An Automatic System for Modality and Negation Detection. In CLEF (Online Working Notes/Labs/Workshop).
  129. Bhaskar, P., Nongmeikapam, K., & Bandyopadhyay, S. (2012, December). Keyphrase extraction in scientific articles: A supervised approach. In Proceedings of COLING 2012: Demonstration Papers (pp. 17-24).
  130. Patra, B. G., Debbarma, K., Das, D., & Bandyopadhyay, S. (2012, December). Part of speech (pos) tagger for kokborok. In Proceedings of COLING 2012: Posters (pp. 923-932).
  131. Nongmeikapam, K., & Bandyopadhyay, S. (2012, September). SVM based Manipuri POS tagging using SVM based identified reduplicated MWE (RMWE). In Proceedings of the CUBE International Information Technology Conference (pp. 272-277). https://doi.org/10.1145/2381716.2381767
  132. Pal, S., & Bandyopadhyay, S. (2012, April). Bootstrapping method for chunk alignment in phrase based SMT. In Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra) (pp. 93-100).
  133. Poria, S., Gelbukh, A., Cambria, E., Das, D., & Bandyopadhyay, S. (2012, December). Enriching SenticNet polarity scores through semi-supervised fuzzy clustering. In 2012 IEEE 12th International Conference on Data Mining Workshops (pp. 709-716). IEEE. https://doi.org/10.1109/ICDMW.2012.142
  134. Das D., Roy S., Bandyopadhyay S. (2012) Emotion Tracking on Blogs – A Case Study for Bengali. In: Jiang H., Ding W., Ali M., Wu X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science, vol 7345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31087-4_47
  135. Kundu, A., Das, D., & Bandyopadhyay, S. (2012, December). Speaker identification from film dialogues. In 2012 4th International Conference on Intelligent Human Computer Interaction (IHCI) (pp. 1-4). IEEE. https://doi.org/10.1109/IHCI.2012.6481855
  136. Pakray P., Neogi S., Bandyopadhyay S., Gelbukh A. (2013) Recognizing Textual Entailment in Non-english Text via Automatic Translation into English. In: Batyrshin I., Mendoza M.G. (eds) Advances in Computational Intelligence. MICAI 2012. Lecture Notes in Computer Science, vol 7630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37798-3_3
  137. Pakray P., Pal S., Poria S., Bandyopadhyay S., Gelbukh A. (2013) SMSFR: SMS-Based FAQ Retrieval System. In: Batyrshin I., Mendoza M.G. (eds) Advances in Computational Intelligence. MICAI 2012. Lecture Notes in Computer Science, vol 7630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37798-3_4
  138. Poria S., Gelbukh A., Das D., Bandyopadhyay S. (2013) Fuzzy Clustering for Semi-supervised Learning – Case Study: Construction of an Emotion Lexicon. In: Batyrshin I., González Mendoza M. (eds) Advances in Artificial Intelligence. MICAI 2012. Lecture Notes in Computer Science, vol 7629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37807-2_7
  139. Das D., Poria S., Bandyopadhyay S. (2012) A Classifier Based Approach to Emotion Lexicon Construction. In: Bouma G., Ittoo A., Métais E., Wortmann H. (eds) Natural Language Processing and Information Systems. NLDB 2012. Lecture Notes in Computer Science, vol 7337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31178-9_41
  140. Patra, B. G., Debbarma, K., Debbarma, S., Das, D., Das, A., & Bandyopadhyay, S. (2012, September). A light weight stemmer in kokborok. In Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012) (pp. 318-325).
  141. Neogi, S., Pakray, P., Bandyopadhyay, S., & Gelbukh, A. (2012). JU_CSE_NLP: multi-grade classification of semantic similarity between text pairs. In * SEM 2012: The First Joint Conference on Lexical and Computational Semantics–Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012) (pp. 571-574).
  142. Neogi, S., Pakray, P., Bandyopadhyay, S., & Gelbukh, A. (2012). JU_CSE_NLP: language independent cross-lingual textual entailment system. In * SEM 2012: The First Joint Conference on Lexical and Computational Semantics–Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012) (pp. 689-695).
  143. Das, A., Bandyopadhyay, S., & Gambäck, B. (2012, June). Sentiment analysis: what is the end user’s requirement?. In Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics (pp. 1-10). https://doi.org/10.1145/2254129.2254173
  144. Banerjee, S., & Bandyopadhyay, S. (2012, December). Bengali question classification: Towards developing qa system. In Proceedings of the 3rd Workshop on South and Southeast Asian Natural Language Processing (pp. 25-40).
  145. Debbarma, K., Patra, B. G., Das, D., & Bandyopadhyay, S. (2012, December). Morphological Analyzer for Kokborok. In Proceedings of the 3rd Workshop on South and Southeast Asian Natural Language Processing (pp. 41-52).
  146. Nongmeikapam, K., RK, V. R., Nirmal, Y., & Bandyopadhyay, S. (2012, December). Manipuri morpheme identification. In Proceedings of the 3rd Workshop on South and Southeast Asian Natural Language Processing (pp. 95-108).
  147. Nongmeikapam, K., RK, V. R., Singh, O. I., & Bandyopadhyay, S. (2012). Automatic Segmentation of Manipuri (Meiteilon) Word into Syllabic Units. arXiv preprint arXiv:1207.3932.
  148. Poria, S., Gelbukh, A., Das, D., & Bandyopadhyay, S. (2012, October). Fuzzy clustering for semi-supervised learning–case study: Construction of an emotion lexicon. In Mexican International Conference on Artificial Intelligence (pp. 73-86). Springer, Berlin, Heidelberg.
  149. Patra, Braja Gopal, et al. “A light weight stemmer in kokborok.” Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012). 2012.
  150. Banerjee, Somnath, and Sivaji Bandyopadhyay. “Question classification and answering from procedural text in english.” In Proceedings of the Workshop on Question Answering for Complex Domains, pp. 11-26. 2012.
  151. Bandyopadhyay, S. (Ed.). (2012). Emerging Applications of Natural Language Processing: Concepts and New Research: Concepts and New Research. IGI Global.
  152. Poria, S., Gelbukh, A., Das, D., & Bandyopadhyay, S. (2012, October). Fuzzy clustering for semi-supervised learning–case study: Construction of an emotion lexicon. In Mexican International Conference on Artificial Intelligence (pp. 73-86). Springer, Berlin, Heidelberg.
  153. Das, Dipankar, Sagnik Roy, and Sivaji Bandyopadhyay. “Emotion tracking on blogs-a case study for bengali.” International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. Springer, Berlin, Heidelberg, 2012.
  154. Sarkar, S., & Bandyopadhyay, S. (2012). FIRE 2012 working notes: Morpheme extraction task using mulaadhaar–a rule-based stemmer for bengali. In Working Notes for the FIRE 2012 Workshop.
  155. Nongmeikapam K., Nonglenjaoba L., Roshan A., Singh T.S., Singh T.N., Bandyopadhyay S. (2012) Transliterated SVM Based Manipuri POS Tagging. In: Wyld D., Zizka J., Nagamalai D. (eds) Advances in Computer Science, Engineering & Applications. Advances in Intelligent and Soft Computing, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30157-5_98
  156. Das, D., Poria, S., Dasari, C. M., & Bandyopadhyay, S. (2012). Building resources for multilingual affect analysis–a case study on hindi, bengali and telugu. In Workshop Programme (p. 54).
  157. Pakray, Partha, Snehasis Neogi, Pinaki Bhaskar, Soujanya Poria, Sivaji Bandyopadhyay, and Alexander F. Gelbukh. “A Textual Entailment System using Anaphora Resolution.” In TAC. 2011.
  158. Das, D., & Bandyopadhyay, S. (2011, November). Analyzing Emotional Statements–Roles of General and Physiological Variables. In Proceedings of the Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2011) (pp. 59-67).
  159. Pal, B. C., Bhaskar, P., & Bandyopadhyay, S. (2011, November). A rule based approach for analysis of comparative or evaluative questions in tourism domain. In Proceedings of the KRAQ11 workshop (pp. 29-37).
  160. Chakraborty, T., Pal, S., Mondal, T., Saikh, T., & Bandyopadhyay, S. (2011, June). Measuring the compositionality of bigrams using statistical methodologies: shared task system description. In Proceedings of the Workshop on Distributional Semantics and Compositionality (pp. 38-42).
  161. Chakraborty, T., Pal, S., Mondal, T., Saikh, T., & Bandyopadhyay, S. (2011, June). Shared task system description: Measuring the Compositionality of Bigrams using Statistical Methodologies. In Proceedings of the Workshop on Distributional Semantics and Compositionality (pp. 38-42).
  162. Torii, Y., Das, D., Bandyopadhyay, S., & Okumura, M. (2011, June). Developing japanese wordnet affect for analyzing emotions. In Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2.011) (pp. 80-86).
  163. Nongmeikapam, K., Singh, N. H., Thoudam, S., & Bandyopadhyay, S. (2011, March). Manipuri transliteration from Bengali script to Meitei Mayek: A rule based approach. In International Conference on Information Systems for Indian Languages (pp. 195-198). Springer, Berlin, Heidelberg.
  164. Nongmeikapam, Kishorjit, Tontang Shangkhunem, Ngariyanbam Mayekleima Chanu, Laishram Newton Singh, Bishworjit Salam, and Sivaji Bandyopadhyay. “CRF Based Name Entity Recognition (NER) in Manipuri.” (2011).
  165. Das, D., Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2011, February). Temporal analysis of sentiment events–a visual realization and tracking. In International Conference on Intelligent Text Processing and Computational Linguistics (pp. 417-428). Springer, Berlin, Heidelberg.
  166. Pakray, Partha, Sivaji Bandyopadhyay, and Alexander Gelbukh. “Textual entailment using lexical and syntactic similarity.” International Journal of Artificial Intelligence and Applications 2, no. 1 (2011): 43-58.
  167. Kolya, A. K., Das, D., Ekbal, A., & Bandyopadhyay, S. (2011, June). Identifying event-sentiment association using lexical equivalence and co-reference approaches. In Proceedings of the ACL 2011 Workshop on Relational Modelsof Semantics (pp. 19-27).
  168. Das, A., & Bandyopadhyay, S. (2011, June). Dr Sentiment knows everything!. In Proceedings of the ACL-HLT 2011 System Demonstrations (pp. 50-55).
  169. Das, D., & Bandyopadhyay, S. (2011, July). Emotions on Bengali blog texts: role of holder and topic. In 2011 International Conference on Advances in Social Networks Analysis and Mining (pp. 587-592). IEEE. https://doi.org/10.1109/ASONAM.2011.106
  170. Nongmeikapam K., Laishram D., Singh N.B., Chanu N.M., Bandyopadhyay S. (2011) Identification of Reduplicated Multiword Expressions Using CRF. In: Gelbukh A.F. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19400-9_4
  171. Pakray P., Gelbukh A., Bandyopadhyay S. (2011) Answer Validation Using Textual Entailment. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6609. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19437-5_29
  172. Das D., Kolya A.K., Ekbal A., Bandyopadhyay S. (2011) Temporal Analysis of Sentiment Events – A Visual Realization and Tracking. In: Gelbukh A.F. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19400-9_33
  173. Ghosh, A., Bhaskar, P., Pal, S., & Bandyopadhyay, S. (2011). Rule based plagiarism detection using information retrieval. Petras et al.
  174. Pakray, P., Bhaskar, P., Banerjee, S., Pal, B. C., Bandyopadhyay, S., & Gelbukh, A. F. (2011, September). A Hybrid Question Answering System based on Information Retrieval and Answer Validation. In CLEF (Notebook Papers/Labs/Workshop) (Vol. 96).
  175. Bhaskar, P., Ghosh, A., Pal, S., & Bandyopadhyay, S. (2011, September). May I check the English of your paper!!!. In Proceedings of the 13th European Workshop on Natural Language Generation (pp. 250-253).
  176. Singh, T. D., & Bandyopadhyay, S. (2011, November). Integration of reduplicated multiword expressions and named entities in a phrase based statistical machine translation system. In Proceedings of 5th international joint conference on natural language processing (pp. 1304-1312).
  177. Bhaskar P., Banerjee S., Neogi S., Bandyopadhyay S. (2012) A Hybrid QA System with Focused IR and Automatic Summarization for INEX 2011. In: Geva S., Kamps J., Schenkel R. (eds) Focused Retrieval of Content and Structure. INEX 2011. Lecture Notes in Computer Science, vol 7424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35734-3_18
  178. Pakray P., Barman U., Bandyopadhyay S., Gelbukh A. (2011) A Statistics-Based Semantic Textual Entailment System. In: Batyrshin I., Sidorov G. (eds) Advances in Artificial Intelligence. MICAI 2011. Lecture Notes in Computer Science, vol 7094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25324-9_23
  179. Pal, S., Chakraborty, T., & Bandyopadhyay, S. (2011). Handling multiword expressions in phrase-based statistical machine translation. Machine Translation Summit XIII, 215-224.
  180. Chakraborty, T., Das, D., & Bandyopadhyay, S. (2011, June). Semantic clustering: an attempt to identify multiword expressions in Bengali. In Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World (pp. 8-13).
  181. Pakray, P., Neogi, S., Bandyopadhyay, S., & Gelbukh, A. F. (2011, December). A Textual Entailment System using Web based Machine Translation System. In NTCIR.
  182. Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2011, September). A hybrid approach for event extraction and event actor identification. In Proceedings of the International Conference Recent Advances in Natural Language Processing 2011 (pp. 592-597).
  183. Pakray, P., Bandyopadhyay, S., & Gelbukh, A. (2010, July). A hybrid textual entailment system using lexical and syntactic features. In 9th IEEE International Conference on Cognitive Informatics (ICCI’10) (pp. 291-296). IEEE. https://doi.org/10.1109/COGINF.2010.5599726
  184. Das, A., Saikh, T., Mondal, T., Ekbal, A., & Bandyopadhyay, S. (2010, July). English to Indian languages machine transliteration system at NEWS 2010. In Proceedings of the 2010 Named Entities Workshop (pp. 71-75).
  185. Pakray P., Gelbukh A., Bandyopadhyay S. (2010) A Syntactic Textual Entailment System Based on Dependency Parser. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2010. Lecture Notes in Computer Science, vol 6008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12116-6_22
  186. Das D., Bandyopadhyay S. (2010) Emotion Holder for Emotional Verbs – The Role of Subject and Syntax. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2010. Lecture Notes in Computer Science, vol 6008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12116-6_32
  187. Das, D., & Bandyopadhyay, S. (2010, October). Extracting emotion topics from blog sentences: use of voting from multi-engine supervised classifiers. In Proceedings of the 2nd international workshop on Search and mining user-generated contents (pp. 119-126). https://doi.org/10.1145/1871985.1872004
  188. Pakray, P., Bhaskar, P., Pal, S., Das, D., Bandyopadhyay, S., & Gelbukh, A. F. (2010, January). JU_CSE_TE: System Description QA@ CLEF 2010-ResPubliQA. In CLEF (Notebook Papers/LABs/Workshops).
  189. Das, A., & Bandyopadhyay, S. (2010, August). Topic-based Bengali opinion summarization. In Coling 2010: Posters (pp. 232-240).
  190. Das, A., Saikh, T., Mondal, T., & Bandyopadhyay, S. (2010). JU_CSE_GREC10: named entity generation at GREC 2010. In Proceedings of the 6th International Natural Language Generation Conference.
  191. Das D., Bandyopadhyay S. (2010) Sentence to Document Level Emotion Tagging – A Coarse-Grained Study on Bengali Blogs. In: Martínez-Trinidad J.F., Carrasco-Ochoa J.A., Kittler J. (eds) Advances in Pattern Recognition. MCPR 2010. Lecture Notes in Computer Science, vol 6256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15992-3_35
  192. Ríos Gaona M.A., Gelbukh A., Bandyopadhyay S. (2010) Recognizing Textual Entailment with Statistical Methods. In: Martínez-Trinidad J.F., Carrasco-Ochoa J.A., Kittler J. (eds) Advances in Pattern Recognition. MCPR 2010. Lecture Notes in Computer Science, vol 6256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15992-3_39
  193. Ríos Gaona M.A., Gelbukh A., Bandyopadhyay S. (2010) Recognizing Textual Entailment Using a Machine Learning Approach. In: Sidorov G., Hernández Aguirre A., Reyes García C.A. (eds) Advances in Soft Computing. MICAI 2010. Lecture Notes in Computer Science, vol 6438. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16773-7_15
  194. Das, D., Pal, S., Mondal, T., Chakraborty, T., & Bandyopadhyay, S. (2010, August). Automatic extraction of complex predicates in Bengali. In Proceedings of the 2010 Workshop on Multiword Expressions: from Theory to Applications (pp. 37-45).
  195. Pal, S., Kumar Naskar, S., Pecina, P., Bandyopadhyay, S., & Way, A. (2010). Handling named entities and compound verbs in phrase-based statistical machine translation. Association for Computational Linguistics.
  196. Chakraborty, T., & Bandyopadhyay, S. (2010, August). Identification of reduplication in Bengali corpus and their semantic analysis: A rule based approach. In Proceedings of the 2010 Workshop on Multiword Expressions: from Theory to Applications (pp. 73-76).
  197. Das, D., & Bandyopadhyay, S. (2010, August). Identifying emotion topic—An unsupervised hybrid approach with Rhetorical Structure and Heuristic Classifier. In Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering (NLPKE-2010) (pp. 1-8). IEEE. https://doi.org/10.1109/NLPKE.2010.5587777
  198. Das, A., Ghosh, A., & Bandyopadhyay, S. (2010, August). Semantic role labeling for Bengali using 5Ws. In Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering (NLPKE-2010) (pp. 1-8). IEEE. https://doi.org/10.1109/NLPKE.2010.5587772
  199. Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2010, August). Event-event relation identification: A crf based approach. In Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering (NLPKE-2010) (pp. 1-8). IEEE. https://doi.org/10.1109/NLPKE.2010.5587774
  200. Das, D., & Bandyopadhyay, S. (2010, November). Identifying emotional expressions, intensities and sentence level emotion tags using a supervised framework. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation (pp. 95-104).
  201. Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2010, November). A Supervised Machine Learning Approach for Event-Event Relation Identification. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation (pp. 447-454).
  202. Bhaskar, P., & Bandyopadhyay, S. (2010, November). A query focused multi document automatic summarization. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation (pp. 545-554).
  203. Das, D., & Bandyopadhyay, S. (2010, November). Finding emotion holder from bengali blog texts—an unsupervised syntactic approach. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation (pp. 621-628).
  204. Das, A., & Bandyopadhyay, S. (2010, November). Towards the global SentiWordNet. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation (pp. 799-808).
  205. Das, D., & Bandyopadhyay, S. (2010, September). Discerning Emotions of Bloggers based on Topics–a Supervised Coreference Approach in Bengali. In ROCLING 2010 Poster Papers (pp. 350-363).
  206. Pal, S., Pakray, P., Das, D., & Bandyopadhyay, S. (2010, July). JU: a supervised approach to identify semantic relations from paired nominals. In Proceedings of the 5th International Workshop on Semantic Evaluation (pp. 206-209).
  207. Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2010, July). JU_CSE_TEMP: a first step towards evaluating events, time expressions and temporal relations. In Proceedings of the 5th International Workshop on Semantic Evaluation (pp. 345-350).
  208. Das, A., & Bandyopadhyay, S. (2010, August). Opinion summarization in Bengali: a theme network model. In 2010 IEEE Second International Conference on Social Computing (pp. 675-682). IEEE. https://doi.org/10.1109/SocialCom.2010.104
  209. Singh, T. D., & Bandyopadhyay, S. (2010, August). Manipuri-english bidirectional statistical machine translation systems using morphology and dependency relations. In Proceedings of the 4th Workshop on Syntax and Structure in Statistical Translation (pp. 83-91).
  210. Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2010, September). Event-time relation identification using machine learning and rules. In International Conference on Text, Speech and Dialogue (pp. 117-124). Springer, Berlin, Heidelberg.
  211. Pakray, P., Pal, S., Poria, S., Bandyopadhyay, S., & Gelbukh, A. F. (2010). JU_CSE_TAC: Textual Entailment Recognition System at TAC RTE-6. In TAC.
  212. Pakray, Partha, Sivaji Bandyopadhyay, and Alexander Gelbukh. “Dependency parser based textual entailment system.” 2010 International Conference on Artificial Intelligence and Computational Intelligence. Vol. 1. IEEE, 2010.https://doi.org/10.1109/AICI.2010.89
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  214. Pakray, Partha, Santanu Pal, Sivaji Bandyopadhyay, and Alexander Gelbukh. “Automatic answer validation system on english language.” In 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), vol. 6, pp. V6-329. IEEE, 2010.https://doi.org/10.1109/ICACTE.2010.5579166
  215. Pakray, Partha, Sivaji Bandyopadhyay, and Alexander Gelbukh. “Textual Entailment and anaphora resolution.” In 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), vol. 6, pp. V6-334. IEEE, 2010.https://doi.org/10.1109/ICACTE.2010.5579163
  216. Das, D., & Bandyopadhyay, S. (2010, August). Labeling emotion in Bengali blog corpus–a fine grained tagging at sentence level. In Proceedings of the Eighth Workshop on Asian Language Resouces (pp. 47-55).
  217. Das, Amitava, and Sivaji Bandyopadhyay. “Semanticnet-perception of human pragmatics.” In Proceedings of the 2nd Workshop on Cognitive Aspects of the Lexicon, pp. 2-11. 2010.
  218. Ghosh, A., Das, A., & Bandyopadhyay, S. (2010, August). Clause identification and classification in bengali. In Proceedings of the 1st Workshop on South and Southeast Asian Natural Language Processing (pp. 17-25).
  219. Singh, T. D., & Bandyopadhyay, S. (2010, August). Web Based Manipuri Corpus for Multiword NER and Reduplicated MWEs Identification using SVM. In Proceedings of the 1st workshop on South and Southeast Asian natural language processing (pp. 35-42).
  220. Das, A., & Bandyopadhyay, S. (2010, August). SentiWordNet for Indian languages. In Proceedings of the eighth workshop on Asian language resouces (pp. 56-63).
  221. Das, A., & Bandyopadhyay, S. (2010, May). Opinion-polarity identification in bengali. In International Conference on Computer Processing of Oriental Languages (pp. 169-182).
  222. Das, D., & Bandyopadhyay, S. (2010, March). Emotion holder for emotional verbs–the role of subject and syntax. In International Conference on Intelligent Text Processing and Computational Linguistics (pp. 385-393). Springer, Berlin, Heidelberg.https://doi.org/10.1007/978-3-642-12116-6_32
  223. Pakray P., Gelbukh A., Bandyopadhyay S. (2010) A Syntactic Textual Entailment System Based on Dependency Parser. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2010. Lecture Notes in Computer Science, vol 6008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12116-6_22
  224. Das, A., & Bandyopadhyay, S. (2010). Sentiwordnet for bangla. Knowledge Sharing Event-4: Task, 2, 1-8.
  225. Banerjee, S., Das, D., & Bandyopadhyay, S. (2010). Classification of verbs–towards developing a Bengali verb subcategorization lexicon. In Global WordNet Conference (pp. 76-83).
  226. Neogi, S., Pakray, P., Bandyopadhyay, S., & Gelbukh, A. (2012). JU_CSE_NLP: language independent cross-lingual textual entailment system. In * SEM 2012: The First Joint Conference on Lexical and Computational Semantics–Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012) (pp. 689-695).
  227. Das, Dipankar, and Sivaji Bandyopadhyay. “Identifying emotion holder and Topic from Bengali emotional sentences.” ICON (2010).
  228. Das, D., & Bandyopadhyay, S. (2010). Developing bengali wordnet affect for analyzing emotion. In International Conference on the Computer Processing of Oriental Languages (pp. 35-40).
  229. Bhaskar, Pinaki, Amitava Das, Partha Pakray, and Sivaji Bandyopadhyay. “Theme based english and bengali ad-hoc monolingual information retrieval in fire 2010.” Corpus 1 (2010): 25-586.
  230. Kishorjit, N., and B. Sivaji. “Identification of MWEs Using CRF in Manipuri and Improvement Using Reduplicated MWEs.” the Proceedings of 8th International Conference on Natural Language (ICON-2010), IIT Kharagpur, India, pp51-57. 2010.
  231. Ghosh, A., Das, A., Bhaskar, P., & Bandyopadhyay, S. (2010). Bengali Parsing System at ICON NLP Tool Contest 2010. ICON10 NLP TOOLS CONTEST: INDIAN LANGUAGE DEPENDENCY PARSING, 960(7269), 20.
  232. Das, A., & Bandyopadhyay, S. (2010). Subjectivity detection using genetic algorithm. Computational Approaches to Subjectivity and Sentiment Analysis, 14.
  233. Das, A., & Bandyopadhyay, S. (2010). Morphological stemming cluster identification for Bangla. Knowledge Sharing Event-1: Task, 3.
  234. Sing, Thoudam Doren, and Sivaji Bandyopadhyay. “Statistical machine translation of English–Manipuri using morpho-syntactic and semantic information.” Proceedings of the Association for Machine Translation in the Americas (AMTA 2010) (2010).
  235. Ghosh, A., Das, A., Bhaskar, P., & Bandyopadhyay, S. (2009). Dependency parser for bengali: the ju system at icon 2009. NLP tool contest ICON, 2009, 87-91.
  236. Das, A., & Bandyopadhyay, S. (2009). Subjectivity detection in english and bengali: A crf-based approach. Proceeding of ICON.
  237. Gaona, M. Á. R., Gelbukh, A., & Bandyopadhyay, S. (2009, November). Web-based variant of the lesk approach to word sense disambiguation. In 2009 Eighth Mexican International Conference on Artificial Intelligence (pp. 103-107). IEEE. https://doi.org/10.1109/MICAI.2009.41
  238. Pakray, P., Bandyopadhyay, S., & Gelbukh, A. F. (2009, November). Lexical based two-way RTE System at RTE-5. In TAC.
  239. Kolya, A. K., Ekbal, A., & Bandyopadhyay, S. (2009, October). A simple approach for Monolingual Event Tracking system in Bengali. In 2009 Eighth International Symposium on Natural Language Processing (pp. 48-53). IEEE. https://doi.org/10.1109/SNLP.2009.5340908
  240. Gupta, S., & Bandyopadhyay, S. (2009, August). Junlg-msr: A machine learning approach of main subject reference selection with rule based improvement. In Proceedings of the 2009 Workshop on Language Generation and Summarisation (UCNLG+ Sum 2009) (pp. 103-104).
  241. Bandyopadhyay, S., Bhattacharyya, P., Varma, V., Sarkar, S., Kumaran, A., & Udupa, R. (2009, June). Proceedings of the Third International Workshop on Cross Lingual Information Access: Addressing the Information Need of Multilingual Societies (CLIAWS3). In Proceedings of the Third International Workshop on Cross Lingual Information Access: Addressing the Information Need of Multilingual Societies (CLIAWS3).
  242. Das, D., & Bandyopadhyay, S. (2009). Emotion Tagging–A Comparative Study on Bengali and English Blogs. In International Conference on Natural Language Processing (pp. 177-184).
  243. Bandyopadhyay, S., Poibeau, T., Saggion, H., & Yangarber, R. (2008, August). Coling 2008: Proceedings of the Workshop Multi-source Multilingual Information Extraction and Summarization. In Coling 2008: Proceedings of the workshop Multi-source Multilingual Information Extraction and Summarization.
  244. Das, D., & Bandyopadhyay, S. (2009, September). Sentence level emotion tagging. In 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops (pp. 1-6). IEEE. https://doi.org/10.1109/ACII.2009.5349598
  245. Das, A., & Bandyopadhyay, S. (2009, September). Theme detection an exploration of opinion subjectivity. In 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops (pp. 1-6). IEEE. https://doi.org/10.1109/ACII.2009.5349599
  246. Das, D., & Bandyopadhyay, S. (2009, August). Word to sentence level emotion tagging for bengali blogs. In Proceedings of the ACL-IJCNLP 2009 Conference Short Papers (pp. 149-152).
  247. Banerjee, S., Das, D., & Bandyopadhyay, S. (2009, August). Bengali verb subcategorization frame acquisition-a baseline model. In Proceedings of the 7th Workshop on Asian Language Resources (ALR7) (pp. 76-83).
  248. Das, A., Ekbal, A., Mondal, T., & Bandyopadhyay, S. (2009, August). English to Hindi machine transliteration system at NEWS 2009. In Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration (NEWS 2009) (pp. 80-83).
  249. Ekbal, A., & Bandyopadhyay, S. (2009, August). Voted NER system using appropriate unlabeled data. In Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration (NEWS 2009) (pp. 202-210).
  250. Ekbal, A., & Bandyopadhyay, S. (2009, February). Bengali named entity recognition using classifier combination. In 2009 Seventh International Conference on Advances in Pattern Recognition (pp. 259-262). IEEE. https://doi.org/10.1109/ICAPR.2009.86
  251. Ekbal A., Bandyopadhyay S. (2009) Improving the Performance of a NER System by Post-processing, Context Patterns and Voting. In: Li W., Mollá-Aliod D. (eds) Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy. ICCPOL 2009. Lecture Notes in Computer Science, vol 5459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00831-3_5
  252. Das D., Ekbal A., Bandyopadhyay S. (2009) Acquiring Verb Subcategorization Frames in Bengali from Corpora. In: Li W., Mollá-Aliod D. (eds) Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy. ICCPOL 2009. Lecture Notes in Computer Science, vol 5459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00831-3_39
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  254. Ekbal, A., Hasanuzzaman, M., & Bandyopadhyay, S. (2009, December). Voted approach for part of speech tagging in bengali. In Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, Volume 1 (pp. 120-129). https://aclanthology.org/Y09-1014
  255. Singh, T. D., Nongmeikapam, K., Ekbal, A., & Bandyopadhyay, S. (2009, December). Named entity recognition for manipuri using support vector machine. In Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, Volume 2 (pp. 811-818). https://aclanthology.org/Y09-2045
  256. Ekbal, A., & Bandyopadhyay, S. (2008). Development of bengali named entity tagged corpus and its use in ner systems. In Proceedings of the 6th Workshop on Asian Language Resources. https://aclanthology.org/I08-7001
  257. Ekbal, A., & Bandyopadhyay, S. (2008, December). Part of speech tagging in bengali using support vector machine. In 2008 International Conference on Information Technology (pp. 106-111). IEEE.
  258. Ekbal, A., Haque, R., Das, A., Poka, V., & Bandyopadhyay, S. (2008). Language independent named entity recognition in indian languages. In Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages.
  259. Ekbal, A., & Bandyopadhyay, S. (2008). Bengali named entity recognition using support vector machine. In Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages.
  260. Paladhi, S., & Bandyopadhyay, S. (2008). A Document Graph Based Query Focused Multi-Document Summarizer. In Proceedings of the 2nd workshop on Cross Lingual Information Access (CLIA) Addressing the Information Need of Multilingual Societies.
  261. Sarkar, S., & Bandyopadhyay, S. (2008). Design of a rule-based stemmer for natural language text in bengali. In Proceedings of the IJCNLP-08 workshop on NLP for Less Privileged Languages. https://aclanthology.org/I08-3012
  262. Bandyopadhyay, S., Mondal, T., Naskar, S. K., Ekbal, A., Haque, R., & Godavarthy, S. R. (2008). Bengali, Hindi and Telugu to English Ad-hoc Bilingual task. In Proceedings of the 2nd workshop on Cross Lingual Information Access (CLIA) Addressing the Information Need of Multilingual Societies.
  263. Singh, T. D., & Bandyopadhyay, S. (2008). Morphology driven manipuri pos tagger. In Proceedings of the IJCNLP-08 Workshop on NLP for less privileged languages. https://aclanthology.org/I08-3015
  264. Ekbal, A., Haque, R., & Bandyopadhyay, S. (2008). Named entity recognition in Bengali: A conditional random field approach. In Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II. https://aclanthology.org/I08-2077
  265. Paladhi, S., & Bandyopadhyay, S. (2008). Generation of Referring Expression Using Prefix Tree Structure. In Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II. https://aclanthology.org/I08-2095
  266. Paladhi, S., & Bandyopadhyay, S. (2008, June). JU-PTBSGRE: GRE using prefix tree based structure. In Proceedings of the Fifth International Natural Language Generation Conference (pp. 230-231). https://aclanthology.org/W08-1139
  267. Ekbal, A., & Bandyopadhyay, S. (2008, November). Multi-Engine Approach for Named Entity Recognition in Bengali. In Proceedings of the 22nd Pacific Asia Conference on Language, Information and Computation (pp. 169-178). https://aclanthology.org/Y08-1016
  268. Ekbal A., Bandyopadhyay S. (2008) Improving the Performance of a NER System by Post-processing and Voting. In: da Vitoria Lobo N. et al. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science, vol 5342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89689-0_87
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  271. Poibeau, T., Bandyopadhyay, S., Saggion, H., & Yangarber, R. (2008). Proceedings of the 2nd workshop on Multi-source, Multilingual Information Extraction and Summarization. COLING-ACL.
  272. Singh, T. D., Ekbal, A., & Bandyopadhyay, S. (2008). Manipuri POS tagging using CRF and SVM: A language independent approach. In proceeding of 6th International conference on Natural Language Processing (ICON-2008) (pp. 240-245).
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  275. Ekbal, A., Mondal, S., & Bandyopadhyay, S. (2007). POS Tagging using HMM and Rule-based Chunking. The Proceedings of SPSAL, 8(1), 25-28.
  276. Ekbal, A., & Bandyopadhyay, S. (2007). Transliteration of Named Entity: Bengali and English as Case Study. In FLAIRS Conference (pp. 223-228).
  277. Ekbal, A., & Bandyopadhyay, S. (2007). Lexicon Development and POS Tagging Using a Tagged Bengali News Corpus. In FLAIRS Conference (pp. 261-262).
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BOOK CHAPTER

  1. Mathematical Information Retrieval: Trends and Techniques”, Pankaj Dadure, Partha Pakray, and Sivaji Bandyopadhyay. In the book, “Deep Natural Language Processing and AI Applications for Industry 5.0″ – IGI Global, DOI: 10.4018/978-1-7998-7728-8, June 2021
  2. Game Based Learning: A Future Research Agenda”, Pankaj Dadure, Partha Pakray, and Sivaji Bandyopadhyay. In the book, “Machine Learning Approaches for Improvising Modern Learning Systems” – IGI Global, DOI: 10.4018/978-1-7998-5009-0, Pp 50-71, May 2021
  3. Heal Favor: A Chatbot Application in Healthcare”, Abdullah Faiz Ur Rahman Khilji, Sahinur Rahman Laskar, Partha Pakray et al.  Book Name: CRC Press book on “Analysis of medical modalities for improved diagnosis in modern healthcare”, ISBN 9780367705367, August 13, 2021, Forthcoming by CRC Press