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Course ID:IT632
Course: Language Technologies on the Web
Instuctor: Prof. Pushpak Bhattacharyya
Prerequesites: None
Contents:
  • This course aims at introducing students to the area of Natural Language Processing that operates at the level of the large amount of text on the web. This involves improving the precision and recall of retrieved documents using language modeling, Handling extremely large volumes of text data for classification and clustering, Automatic summary generation, Providing translation/ translation support, Cross lingual Information Retrieval and so on and so forth.
    All the above are cutting edge research areas and need, besides other techniques, language processing abilities. However, since the processing needs to be done on large volume of text in a robust and scalable manner, statistical and probabilistic methods will be emphasized - along with the NLP fundamentals.
    Syllabus:
    Words, Lexicon Design and Processing, Lexical Semantics Syntax, Parsing Techniques (Chart, ATN etc.), Probabilistic Parsers Semantics, Knoweldge Representation, Frames, Semantic Nets, Noisy Channel Metaphor, Hidden Markov Model and Associated Algorithms, Word Level Processing, Part of Speech Tagging, Parsing Techniques, Probabilistic Parsing, IR and Language Modeling, Corpus Technology, Lexical Knowledge Networks (Wordnet, Conceptnet, Framenet etc.), Machine Translation, question answering and Information Extraction, Indian Language Computing. : 
  • References::
  • Natural Language Understanding. Benjamin/Cummings, 2nd ed.,1995.:  James, Allen
  • Statistical Language Learning, MIT Press, 1996:  Charniak, Eugene
  • Natural Language, 1995:  Bharathi, A., Chaitanya Vineet and Sangal Vineet
  • Speech and Language Processing. Prentice Hall, 2000.:  Jurafsky, Dan and Martin James
  • Foundations of Statistical Natural Language Processing, MIT Press, 1999.:  Manning, Christopher and Heinrich Schutze
  • Journals: Natural Language Engineering, Computational Linguistics, Journal of IR, Journal of MT, IEEE Trans. on Data and Knowlegde Engineering.: 
  • Conferences: SIGIR, ICML, ACL, EMNLP, HLT: 




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