Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and Machine Learning (ML) are two correlated concepts under Computer Science. These two technologies are the most trending ones for creating intelligent systems.  AI and ML are related to each other but are different in terms of their functions. AI can be defined as a concept that simulates human thinking capability and behaviour, whereas, machine learning is a subset of AI that allows machines to learn from data without being programmed explicitly. Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. AI applications include advanced web search engines (i.e. Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g. Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). As machines become increasingly capable, tasks considered to require “intelligence” are often removed from the definition of AI, a phenomenon known as the AI effect.

Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

Faculty Members:

Publications:

(A few selected papers)

  • K. Yadav and S. K. Borgohain, “Sentence generation from a bag of words using N-gram model,” Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference, Ramanathapuram, 2014, pp. 1771-1776. doi: 10.1109/ICACCCT.2014.7019414
  • Samir Borgohain, Shivashankar B. Nair, An Immuno-inspired approach towards Sentence Generation, Proceedings of the 2015 on Genetic and Evolutionary Computation Conference (GECCO ’15), ACM SIGEVO, New York, NY, USA, pp. 97-104.  doi: http://dx.doi.org/10.1145/2739480.2754805 [Paper Acceptance rate at GECCO] Core Rank: A.
  • Sulabh Katiyar and Samir Borgohain. “Lexical Similarity Based Query-Focused Summarization Using Artificial Immune Systems.” Artificial Intelligence Perspectives and Applications. Springer International Publishing, 2015. 287-296.
  • Manomita Chakraborty, Amit Kumar Verma, Saroj Kr. Biswas, “Breast Cancer Management System using Decision Tree and Neural Network”, SN Computer Science Springer, Accepted
  • Abhinaba Dattachaudhuri, Saroj Kr. Biswas, Manomita Chakraborty, A Transparent Rule Based Expert System Using Neural Network, Soft Computing, Springer, Accepted (SCI journal, IF: 3.050)
  • Debashree Devi, Saroj Kr. Biswas, Biswajit Purakayastha, Correlation-based Oversampling aided Cost Sensitive Ensemble learning technique for Treatment of Class Imbalance, Journal of Experimental & Theoretical Artificial Intelligence, Taylor & Francis, Accepted: (SCI journal, IF: 2.111)
  • Monali Bordoloi, S. K. Biswas, Keyword Extraction using Supervised Cumulative TextRank, Multimedia Tools and Applications, Springer, Accepted (SCI journal, IF: 2.101)
  •  Monali Bordoloi, S. K. Biswas, Graph Based Sentiment Analysis using Keyword Rank based Polarity Assignment, Multimedia Tools and Applications, Springer, Accepted (SCI journal, IF: 2.101)
  • Manomita Chakraborty, Saroj Kr. Biswas, Biswajit Purkayastha, Rule Extraction from Neural Network trained using Deep Belief Network and Back Propagation, Knowledge and Information Systems Springer, Accepted (SCI journal, IF: 2.547)
  •  Rajdeep Ghosh, Nidul Sinha, Saroj Kumar Biswas & Souvik Phadikar, A modified grey wolf optimization based feature selection method from EEG for silent speech classification, Journal of Information and Optimization Sciences Taylor & Francis, Vol. 40 (2019), No. 8, pp. 1639–1652 (ESCI)
  • Manomita Chakraborty, Saroj Kr. Biswas, Biswajit Purkayastha, A Novel Ensembling Method to Boost Performance of Neural Networks, Journal of Experimental & Theoretical Artificial Intelligence, Taylor & Francis, Accepted: doi.org/10.1080/0952813X.2019.1610799 (SCI journal, IF: 2.111)
  • Debashree Devi, Saroj Kr. Biswas, Biswajit Purakayastha, Learning in presence of Class Imbalance and Class Overlapping by using One-class SVM and Undersampling Technique, Connection Science,  vol. 38, no. 3, pp. 1-38, DOI: 10.1080/09540091.2018.1560394, Taylor & Francis, (SCI journal, IF: 0.933)
  • Manomita Chakraborty,   Saroj Kr. Biswas, Biswajit Purkayastha, Rule Extraction from Neural Network using Input Data Ranges Recursively, New Generation Computing,  vol. 37, no.1, pp.  67-96, Springer, (SCI journal, IF: 0.833)
  • Heisnam Rohen Singh, Saroj Kr. Biswas, Rule Extraction from Neuro-fuzzy System for Classification using Feature Weights, International Journal of Fuzzy System Applications (IJFSA), vol. 9, no. 2, IGI Global, (SCOPUS indexed)
  • Rajdeep Ghosh, Vikas Kumar, Nidul Sinha, Saroj Kumar Biswas, Motor imagery task classification using intelligent algorithm with prominent trial selection, Journal of Intelligent and Fuzzy Systems, vol. 35, no. 1, pp. 1-10, 2018 , IOP Press (SCI journal, IF 1.637)
  •  Monali Bordoloi, S. K. Biswas, Keyword Extraction from Microblogs using Collective Weight, Social Network Analysis and Mining, vol. 8, no. 1, 58, Springer, (SCOPUS, ESCI indexed)
  • Rajdeep Ghosh, Nidul Sinha, Saroj Kumar Biswas, Automated Eye Blink Artifact Removal from EEG using Support Vector Machine and Autoencoder, IET Signal Processing, vol. 13, no. 2, pp. 141-148, DOI:  10.1049/iet-spr.2018.5111, (SCI journal, IF 1.754)
  •  Sujit Kumar, Saroj Kr. Biswas, Debashree Devi, TLUSBoost Algorithm: A Boosting Solution for Class Imbalance Problem, Soft Computing, https://doi.org/10.1007/s00500-018-3629-4, 2018, Springer. (SCI journal, IF 3.050)
  •  Nilesh Dilipkumar Gharde, Dalton Meitei Thounaojam, Badal Soni, Saroj K Biswas, Robust perceptual image hashing using fuzzy color histogram, Multimedia Tools and Applications, vol. 77, no. 23, pp. 30815-30840 Springer. (SCI journal, IF 2.101)
  • Saroj Kr. Biswas, Intrusion Detection Using Machine Learning: A Comparison Study, International Journal of Pure and Applied Mathematics.  vol. 118, no. 19 2018, pp. 101-114. (SCOPUS indexed)
  • Heisnam Rohen Singh, Dr. Saroj Kr. Biswas, Transparent Neuro-fuzzy model for Linguistic variables selection and rule-based classification, International Journal of Pure and Applied Mathematics. vol. 118, no. 19, 2018, pp. 85-100. (SCOPUS indexed)
  • Monali Bordoloi, Dr. S. K. Biswas, Sentiment Analysis of Product using Machine Learning Technique: A Comparison among NB, SVM and MaxEnt, International Journal of Pure and Applied Mathematics. vol. 118, no. 19, 2018, pp. 71-83. (SCOPUS indexed)
  • Manomita Chakraborty,   Saroj Kr. Biswas,  Biswajit Purkayastha,    Recursive Rule Extraction from Neural Network using Reverse  Engineering Technique, New Generation Computing,  vol. 36, no. 2, pp. 119-142, Springer (SCI journal, IF: 0.833)
  • Saroj Kr. Biswas,  Monali Bordoloi,   Shreya Jecob,  A      Graph Based Keyword Extraction Model using Collective Node Weight, Expert Systems with Applications, Elsevier, vol. 97, pp. 51-59  (SCI journal, IF: 5.452)
  • Saroj Kr. Biswas, Debashree Devi, Manomita Chakraborty: Hybrid Case Based Reasoning System by Under Sampling and Cost Sensitive Neural Network for Classification, Journal of Organizational and End User Computing, IGI Global, vol. 30, no. 4, pp. 104-122 · October 2018 (SCI journal, IF: 0.759)
  •  Saroj Kr. Biswas, Manomita Chakraborty, Biswajit Purakayastha: Rule Extraction from Neural Network using Classified and Misclassified Data: International Journal on Artificial Intelligence Tools, World Scientific vol. 26, no. 3 pp.1-26, 2017 (SCI journal, IF: 0.778)
  • Saroj Kr. Biswas, Manomita Chakraborty, Biswajit Purakayastha: A Rule generation Algorithm from Neural Network using Classified and Misclassified Data: International Journal of Bio-Inspired Computation, Inderscience, vol. 11 no.1, pp. 60-70, 2018, (SCI journal, IF: 3.395)
  •  Debashree Devi, Saroj Kr. Biswas, Biswajit Purakayastha: REDUNDANCY-DRIVEN MODIFIED TOMEK LINK BASED UNDERSAMPLING: A SOLUTION TO CLASS IMBALANCE, Pattern Recognition Letters, Elsevier, vol. 93, pp. 3-12, 2017 (SCI journal, IF: 3.255  )
  •  Saroj Kr. Biswas, Monali Bordoloi, Biswajit Purakayastha: Review on Feature Selection and Classification using Neuro-Fuzzy Approaches, International Journal of Applied Evolutionary Computation, IGI Global, vol. 7 no. 4, pp. 28-44, 2016.
  •  Heisnam Rohen Singh, Saroj Kr. Biswas, Biswajit Purakayastha: A Neuro-fuzzy Classification Technique using Dynamic Clustering and GSS Rule Generation, Journal of Computational and Applied Mathematics, Elsevier vol. 309, pp. 683-694, 2016-2017 (SCI journal, 5-year IF: 2.014 )
  • Saroj Kr Biswas, Monali Bordoloi, Heisnam Rohen Singh, Biswajit Purkayastha: A Neuro-fuzzy Rule-based Classifier Using Important Features and Top Linguistic Features, International Journal of Intelligent Information Technologies (IJIIT), vol. 12, issue 3  pp. 38-50, 2016, IGI Global (SCOPUS, SSCI(web of science))
  •  Saroj Kr Biswas, Nidul Sinha, Biswajit Purakayastha, Leniency Marbaniang: Weather Prediction by Integrating Recurrent Neural Network Dynamics into Case Based Reasoning, International Journal of Knowledge Based Computer Systems, vol. 4, issue. 1 pp. 1-17, PublishingIndia.com, 2015.
  • Saroj Kr. Biswas, Manomita Chakraborty, Heisnam Rohen Singh, Debashree Devi, Biswajit Purkayastha, Akhil Kr. Das, Hybrid Case Based Reasoning System by Cost Sensitive Neural Network for Classification, Soft computing, Springer, vol. 21, Issue 24, pp. 7579–7596, 2017, (SCI journal, IF 3.050)
  •  Saroj Kr Biswas, Nidul Sinha, Biswajit Purakayastha, Recent trends in CBR, challenges and future directions: a critical review” International Journal of Knowledge Based Computer Systems, PublishingIndia.com, Accepted, 2015, In press.
  • Saroj Kr Biswas, Barnana Baruah, Nidul Sinha and Biswajit Purkayastha, A Hybrid CBR Classification Model by Integrating ANN into CBR, International Journal of Services Technology and Management,Inderscience,vol. 21, Nos. 4/5/6, pp. 272-293, 2015. (SCOPUS, ESCI(web of science))
  • Saroj Kr. Biswas, Barnana Baruah, Biswajit Purkayastha, Manomita Chakraborty, An ANN Based Classification Algorithm for Swine Flu Diagnosis , International Journal of Knowledge Based Computer Systems, PublishingIndia.com, vol. 3, issue 1, pp. 1-12, 2015.
  • Saroj Kr Biswas, Leniency Marbaniang , Biswajit Purkayastha, Manomita Chakraborty, Heisnam Rohen Singh, Monali Bordoloi, Rainfall Forecasting by Relevant Attributes Using Artificial Neural Networks – A Comparative Study, International Journal of Big Data Intelligence,Inderscience, vol.3 no. 2, pp. 111-121, 2015.
  • Saroj Kr Biswas, Nidul Sinha, Biswajit Purakayastha, Leniency Marbaniang, Hybrid expert system using case based reasoning and neural network for classification, Biologically Inspired Cognitive Architectures,Elsevier, vol. 9, pp. 57– 70, 2014 (SCI journal, IF: 1.074)
  •  Saroj K. Biswas, Nidul Sinha, Biswajit Purkayastha, A review on fundamentals of case-based reasoning and its recent application in different domains, International Journal of Advanced Intelligence Paradigms,Inderscience, vol. 6, no.3, pp. 235-254, 2014(SCOPUS journal)
  • Saroj Kr Biswas, Nidul Sinha, Biswajit Purakayastha, Leniency Marbaniang, Weather Prediction by Recurrent Neural Network Dynamics, International Journal of Intelligent Engineering Informatics,Inderscience, vol. 2, nos. 2/3, pp. 166-180, 2014 (ESCI journal).
  •  Saroj K. Biswas, Nidul Sinha, Barnana Baruah, Biswajit Purkayastha, Intelligent Decision Support System of Swine Flu Prediction using Novel Case Classification Algorithm, Int. J. Knowledge Engineering and Data Mining, Inderscience, vol. 3, No. 1, pp. 1-19, 2014.
  • Saroj Kr. Biswas, Akhil Kr. Das, Dr. Biswajit Purkayastha, Dibyendu Barman, Techniques for Efficient Case Retrieval and Rainfall Prediction Using CBR and Fuzzy Logic, International Journal of Electronics Communication and Computer Engineering, vol. 4, issue 3, pp.692-698, 2013.
  • Agarwal, S., Naresh Babu Muppalaneni Portfolio optimization in stocks using mean–variance optimization and the efficient frontier. Int. j. inf. tecnol. (2022). Springer SCOPUS  https://doi.org/10.1007/s41870-022-01052-2
  • Nageshwar Nath Pandey, Naresh Babu Muppalaneni A survey on visual and non-visual features in Driver’s drowsiness detection. Multimedia Tools Applications. Springer (2022). SCIE Indexed, IF: 2.757 https://doi.org/10.1007/s11042-022-13150-1
    http://www.scopus.com/inward/record.url?eid=2-s2.0-85130048273&partnerID=MN8TOARS
  • Nageshwar Nath Pandey, Naresh Babu Muppalaneni “A novel drowsiness detection model using composite features of head, eye, and facial expression” Neural Computing & Applications. Springer (2022). SCIE Indexed, IF: 5.6  https://doi.org/10.1007/s00521-022-07209-1
    http://www.scopus.com/inward/record.url?eid=2-s2.0-85128214513&partnerID=MN8TOARS
  • Nageshwar Nath Pandey, Naresh Babu Muppalaneni “A novel algorithmic approach of open eye analysis for drowsiness detection” International Journal of Information Technology, Springer(2021), SCOPUS https://doi.org/10.1007/s41870-021-00811-x
    http://www.scopus.com/inward/record.url?eid=2-s2.0-85116598680&partnerID=MN8TOARS
  • Prarthana Dutta, Naresh Babu Muppalaneni “DigiNet: Prediction of Assamese handwritten digits using convolutional neural network” Concurrency and Computation: Practice and Experience, Wiley, June 2021,  SCIE, Impact factor 1.537 http://doi.org/10.1002/cpe.6451
    http://www.scopus.com/inward/record.url?eid=2-s2.0-85107869088&partnerID=MN8TOARS
  • Nageshwar Nath Pandey, Naresh Babu Muppalaneni “Temporal and spatial feature based approaches in drowsiness detection using deep learning technique”. Journal of Real-Time Image Processing, Springer (2021). SCIE Indexed, IF: 2.358  
    http://www.scopus.com/inward/record.url?eid=2-s2.0-85105400406&partnerID=MN8TOARS