CS2035 NATURAL LANGUAGE PROCESSING Syllabus

CS2035                 NATURAL LANGUAGE PROCESSING               L T P C   

                                                                                                                  3  0 0 3 

UNIT I                               9
Introduction – Models -and Algorithms - The Turing Test -Regular Expressions
Basic  Regular  Expression  Patterns  -Finite  State  Automata  -Regular  Languages  and
FSAs  –  Morphology  -Inflectional  Morphology  -  Derivational  Morphology  -Finite-State
Morphological Parsing - Combining an FST Lexicon and Rules -Porter Stemmer

UNIT II                               9
N-grams Models  of  Syntax  - Counting Words    - Unsmoothed N-grams  –  Smoothing-
Backoff - Deleted Interpolation – Entropy - English Word Classes - Tagsets for English -
Part  of  Speech  Tagging  -Rule-Based  Part  of  Speech  Tagging  -  Stochastic  Part  of
Speech Tagging - Transformation-Based Tagging -

UNIT III                             9
Context Free Grammars for English Syntax- Context-Free Rules and Trees - Sentence-
Level Constructions –Agreement – Sub Categorization – Parsing – Top-down – Earley
Parsing -Feature Structures - Probabilistic Context-Free Grammars

UNIT IV                             9
Representing Meaning - Meaning Structure of Language - First Order Predicate Calculus
-  Representing  Linguistically  Relevant  Concepts  -Syntax-Driven  Semantic  Analysis  -
Semantic Attachments - Syntax-Driven Analyzer - Robust Analysis - Lexemes and Their
Senses - Internal Structure - Word Sense Disambiguation -Information Retrieval

UNIT V                             9
Discourse  -Reference Resolution  -  Text Coherence  -Discourse Structure  - Dialog and
Conversational  Agents  -  Dialog  Acts  –  Interpretation  –  Coherence  -Conversational
Agents  -  Language  Generation  –  Architecture  -Surface  Realizations  -  Discourse
Planning  –  Machine  Translation  -Transfer  Metaphor  –  Interlingua  –  Statistical
Approaches
          TOTAL: 45 PERIODS
TEXT BOOKS:
1.  D.  Jurafsky  and  J. Martin  “Speech  and  Language  Processing:  An  Introduction  to
Natural Language Processing, Computational Linguistics, and Speech Recognition”,
2.  C.  Manning  and  H.  Schutze,  “Foundations  of  Statistical  Natural  Language
Processing”,

REFERENCE:
1.  James Allen. “Natural Language Understanding”, Addison Wesley, 1994.