Natural Language Processing

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KHUDKIBOOK
NATURAL LANGUAGE PROCESSING 1729505
FREE PDF 1729505
Code: 1729505 Credits: 4 Semester 2 AIAD

Natural Language Processing

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Natural Language Processing Syllabus — Unit-wise Content

The official GTU curriculum for Natural Language Processing (subject code 1729505) as prescribed for AIAD · Semester 2 divides the course into 4 units, covering 63 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (1729505)

Unit 1 Introduction

2 lecture hours

  • Concept and Use of Natural Language Processing
  • Ambiguity and uncertainty in language
  • The Turing test
  • Models and Algorithms

Unit 2 Regular Expressions, Automata and Finite-State Transducers

14 lecture hours

  • Basic Regular Expression Patterns
  • Grouping, and Precedence
  • Advanced Operators
  • Regular Expression Substitution
  • Using FSA to Recognize Sheeptalk
  • Formal Languages
  • Nondeterministic FSAs
  • Using an NFSA to accept strings
  • Recognition as Search
  • Relating Deterministic and Non- deterministic Automata
  • Regular Languages and FSAs
  • Survey of (Mostly) English Morphology
  • Inflectional Morphology
  • Derivational Morphology
  • The Lexicon and Morphotactics
  • Morphological Parsing with Finite-State Transducers
  • Orthographic Rules and Finite-State Transducers
  • Human Morphological Processing
  • N-gram Language Models
  • Text Subject Name : Natural Language Processing Subject Code : 1729505 Normalization
  • Minimum Edit Distance
  • Evaluating Language Models
  • Generalization and Zeros
  • Kneser-Ney Smoothing

Unit 3 Word Classes and Part-of-Speech Tagging

6 lecture hours

  • English Word Classes
  • Tagsets for English
  • Part of Speech Tagging
  • Rule-based Part-of-speech Tagging
  • Stochastic Part-of-speech Tagging
  • The Actual Algorithm for HMM tagging
  • Transformation-Based Tagging
  • How TBL rules are applied
  • How TBL Rules are Learned
  • Multiple tags and multiple words
  • Unknown words
  • Class-based N-grams

Unit 4 Context-Free Grammars, Semantics and Pragmatics

14 lecture hours

  • Context-Free Rules and Trees
  • Sentence-Level Constructions
  • The Noun Phrase
  • The Verb Phrase and Subcategorization
  • Spoken Language Syntax
  • Grammar Equivalence & Normal Form
  • Finite State & Context-Free Grammars
  • Grammars & Human Processing
  • Parsing as Search
  • Top-Down and Bottom-Up Parsing with comparison
  • A Basic Top-down Parser
  • Adding Bottom-up Filtering
  • Problems with the Basic Top-down Parser
  • Left Recursion
  • Syntax-Driven Semantic Analysis
  • Attachments for a Fragment of English
  • Idioms and Compositionality
  • Robust Semantic Analysis
  • WordNet: A Database of Lexical Relations
  • Reference Resolution
  • Text Coherence
  • Discourse Structure
  • Psycholinguistic Studies of Reference and Coherence

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