Natural Language Processing
Natural Language Processing. Instructor: Prof. Pawan Goyal, Department of Computer Science and Engineering, IIT Kharagpur. This course deals with various topics in natural language processing and its applications: basic text processing, spelling correction, language modeling, advanced smoothing for language modeling, Part of Speech tagging, models for sequential tagging, syntax, constituency parsing, dependency parsing, lexical semantics, distributional semantics, topic models, entity linking, information extraction, text summarization, text classification, sentiment analysis and opinion mining.
(from nptel.ac.in)
Lecture 01  Introduction 
Lecture 02  NLP Applications: Machine Translation, Sentiment Analysis 
Lecture 03  Why is NLP Hard?  Ambiguities in Language 
Lecture 04  Empirical Laws: Heap's Law, Zipf's Law, TypeToken Ratio 
Lecture 05  Text Processing: Word toKenization and Segmentation, Lemmatization, Stemming 
Lecture 06  Spelling Correction: Edit Distance  Dynamic Programming Approach 
Lecture 07  Weighted Edit Distance, Finding Dictionary Entries with Small Edit Distances 
Lecture 08  Noisy Channel Model for Spelling Correction 
Lecture 09  NGram Language Model 
Lecture 10  Evolution of Language Models, Basic Smoothing 
Lecture 11  Language Modeling: Advanced Smoothing Models 
Lecture 12  Computational Morphology 
Lecture 13  Finite State Methods for Morphology 
Lecture 14  Introduction to Part of Speech Tagging 
Lecture 15  Hidden Markov Models for PoS Tagging 
Lecture 16  Viterbi Decoding for Hidden Markov Models, Parameter Learning 
Lecture 17  ForwardBackward Algorithm, Baum Welch Algorithm 
Lecture 18  Maximum Entropy Models I 
Lecture 19  Maximum Entropy Models II: Maximum Entropy Markov Model, Beam Search 
Lecture 20  Conditional Random Fields 
Lecture 21  Syntax  Introduction 
Lecture 22  Syntax  Parsing I 
Lecture 23  Syntax  CKY Algorithm, PCFGs 
Lecture 24  PCFGs  InsideOutside Probabilities 
Lecture 25  InsideOutside Probabilities 
Lecture 26 
Lecture 27  Dependency Grammars and Parsing  Introduction 
Lecture 28  Transition based Parsing: Formulation 
Lecture 29  Transition based Parsing: Learning 
Lecture 30  Maximum Spanning Tree (MST) based Dependency Parsing 
Lecture 31  MST based Dependency Parsing: Learning 
Lecture 32  Distributional Semantics  Introduction 
Lecture 33  Distributional Models of Semantics 
Lecture 34  Distributional Semantics: Applications, Structured Models 
Lecture 35  Word Embeddings, Part I 
Lecture 36  Word Embeddings, Part II 
Lecture 37  Lexical Semantics 
Lecture 38  Lexical Semantics  Wordnet 
Lecture 39  Word Sense Disambiguation: Lesk Algorithm, Random Walk Approach, Naive Bayes 
Lecture 40  Word Sense Disambiguation: SemiSupervised and Unsupervised Approaches 
Lecture 41  Novel Word Sense Detection 
Lecture 42  Topic Models  Introduction 
Lecture 43  Latent Dirichlet Allocation: Formulation 
Lecture 44  Gibbs Sampling for LDA, Applications 
Lecture 45  LDA Variants and Applications: Correlated Topic Models, Dynamic Topic Models, Supervised LDA 
Lecture 46  LDA Variants and Applications: Relational Topic Models, Bayesian Nonparametrics 
Lecture 47  Entity Linking: Wikification, Mention Detection, Link Disambiguation, Key Phraseness 
Lecture 48  Entity Linking: Relatedness, Learning to Link 
Lecture 49  Information Extraction: Definition and Applications, Regex, Handbuilt Patterns 
Lecture 50  Bootstrapping and Supervised Relation Extraction 
Lecture 51  Distort Supervision, Freebase, Syntactic Dependency Paths 
Lecture 52  Text Summarization  Concepts, Lexrank, Maximal Marginal Relevance 
Lecture 53  Optimization based Approaches for Summarization 
Lecture 54  Summarization Evaluation: Manual Evaluation, Rouge Evaluation 
Lecture 55  Text Classification: Naive Bayes, Bag of Words, Add One Smoothing 
Lecture 56  Text Classification: Naive Bayes, Multivalue Classification, Confusion Matrix 
Lecture 57  Tokenization and Preprocessing for Sentiment Analysis 
Lecture 58  Sentiment Analysis  Affective Lexicons 
Lecture 59  Learning Affective Lexicons 
Lecture 60  Computing with Affective Lexicons 
Lecture 61  Aspect based Sentiment Analysis 
References 
Natural Language Processing
Instructor: Prof. Pawan Goyal, Department of Computer Science and Engineering, IIT Kharagpur. This course deals with various topics in natural language processing and its applications.
