AI353

Course Name: 

Natural Language Processing (AI353)

Programme: 

B.Tech (AI)

Category: 

Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-0-2) 4

Content: 

Introductory concepts of Linguistic systems, Language Modeling and Sequence tagging, Word stemming, tokenization, normalization, Part of Speech tagging, Traditional models of distributional semantics, Unstructured Text Management, Word and Sentence embeddings, n-gram models, Maximum Entropy models, Hidden Markov Models, Viterbi Algorithm, Neural Language Models; Information Extraction, Named Entity Recognition, Relation Extraction; Understanding Semantics, word sense and word similarity, Lesk Algorithm, Wordnets, Topic Modeling, Dialog Systems, Emerging trends, Research issues, challenges, interesting applications in various domains.

References: 

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
Christopher D. Manning and Hinrich Schütze, "Foundations of Statistical Natural Language Processing" MIT Press, 1999
Tanveer Siddiqui, U.S Tiwary, "Natural Language Processing And Information Retrieval", 1st Ed

Department: 

Information Technology
 

Contact us

Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in
 

Web Admin: Sowmya Kamath S

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