Course Name: 

Topics In Natural Language Processing (IT826)


M.Tech (IT)


Elective Courses (Ele)

Credits (L-T-P): 

(3-0-2) 4


Introduction to Language Modelling, History and Applications, Text Processing Systems and architectures, N-grams, Lexical semantics and word-sense disambiguation, part of speech tagging, spelling correction, Text Classification – basics and process, tools, Naïve Bayes classifier, learning algorithms, Probabilistic Similarity Measures and Clustering, Sentiment Analysis, Generating and developing sentiment lexicons, learning lexicons, Information Retrieval, TF/IDF, Vector Space Models, Query analysis and processing, Information Extraction - Maximum Entropy models, Relation Extraction, Stochastic Tagging, and Log-Linear Models, Introduction to Semantics in NLP, Question Answering Models, passphrase analysis and answer generation, summarization, Emerging trends,research issues, challenges, interesting applications in various domains.


Christopher D. Manning and Hinrich Schütze, Foundations of Statistical Natural Language Processing, MIT Press, 1999
Daniel Jurafsky and James H. Martin. Speech and Language Processing: An Introduction to Natural Language
Processing, Computational Linguistics and Speech Recognition, Second Edition. Prentice Hall, 2008
Steven Bird. Natural Language Processing with Python, O'Reilly, 2009
James Allen, Natural Language Understanding. Benjamin/Cummings, 2ed, 1995


Information Technology

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G. Ram Mohana Reddy

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Department of Information Technology, NITK, Surathkal,
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.
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Email:  infotech[AT]nitk[DOT]ac[DOT]in

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