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Natural Language Processing. Instructor: Prof. Pushpak Bhattacharyya, Department of Computer Science and Engineering, IIT Bombay.
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Description
This course provides an understanding of natural language processing, its tools, techniques, philosophy and principle. Topics covered include sound, words and word forms, structures, meaning, and web 2.0 applications:
Sound: Biology of Speech Processing; Place and Manner of Articulation; Word Boundary Detection; Argmax based computations; HMM and Speech Recognition.
Words and Word Forms: Morphology fundamentals; Morphological Diversity of Indian Languages; Morphology Paradigms; Finite State Machine Based Morphology; Automatic Morphology Learning; Shallow Parsing; Named Entities; Maximum Entropy Models; Random Fields.
Structures: Theories of Parsing, Parsing Algorithms; Robust and Scalable Parsing on Noisy Text as in Web documents; Hybrid of Rule Based and Probabilistic Parsing; Scope Ambiguity and Attachment Ambiguity resolution.
Meaning: Lexical Knowledge Networks, Wordnet Theory; Indian Language Wordnets and Multilingual Dictionaries; Semantic Roles; Word Sense Disambiguation; WSD and Multilinguality; Metaphors; Coreferences.
Web 2.0 Applications: Sentiment Analysis; Text Entailment; Robust and Scalable Machine Translation; Question Answering in Multilingual Setting; Cross Lingual Information Retrieval (CLIR).
Course content
- Lecture 01 – Introduction Unlimited
- Lecture 02 – Stages of NLP Unlimited
- Lecture 03 – Stages of NLP (cont.) Unlimited
- Lecture 04 – Two Approaches to NLP Unlimited
- Lecture 05 – Sequence Labelling and Noisy Channel Unlimited
- Lecture 06 – Noisy Channel: Argmax based Computation Unlimited
- Lecture 07 – Argmax based Computation Unlimited
- Lecture 08 – Noisy Channel Application to NLP Unlimited
- Lecture 09 – Probabilistic Parsing, Part of Speech Tagging Unlimited
- Lecture 10 – Part of Speech Tagging Unlimited
- Lecture 11 – Part of Speech Tagging (cont.) Unlimited
- Lecture 12 – Part of Speech Tagging (cont.), Indian Language in Focus; Morphology Analysis Unlimited
- Lecture 13 – PoS Tagging (cont.), Indian Language Consideration; Accuracy Measure Unlimited
- Lecture 14 – PoS Tagging: Fundamental Principle; Why Challenging; Accuracy Unlimited
- Lecture 15 – PoS Tagging; Accuracy Measurement; Word Categories Unlimited
- Lecture 16 – Artificial Intelligence and Probability; Hidden Markov Model (HMM) Unlimited
- Lecture 17 – Hidden Markov Model (HMM) Unlimited
- Lecture 18 – HMM, Viterbi, Forward-Backward Algorithm Unlimited
- Lecture 19 – HMM, Viterbi, Forward-Backward Algorithm (cont.) Unlimited
- Lecture 20 – HMM, Viterbi, Forward-Backward Algorithms, Baum-Welch Algorithm Unlimited
- Lecture 21 – HMM, Viterbi, Forward-Backward Algorithms, Baum-Welch Algorithm (cont.) Unlimited
- Lecture 22 – Natural Language Processing and Information Retrieval Unlimited
- Lecture 23 – Cross Lingual Information Access (CLIA); Information Retrieval (IR) Basics Unlimited
- Lecture 24 – IR Models: Boolean Vector Unlimited
- Lecture 25 – IR Models: NLP and IR Relationship Unlimited
- Lecture 26 – NLP and IR: How NLP has used IR, toward Latent Semantic Indexing-PCA Unlimited
- Lecture 27 – Least Squares Method; Recap of PCA; Towards Latent Semantic Indexing Unlimited
- Lecture 28 – PCA; SVD; Towards Latent Semantic Indexing Unlimited
- Lecture 29 – Wordnet and Word Sense Disambiguation Unlimited
- Lecture 30 – Wordnet and Word Sense Disambiguation (cont.) Unlimited
- Lecture 31 – Wordnet; Metonymy and Word Sense Disambiguation Unlimited
- Lecture 32 – Word Sense Disambiguation Unlimited
- Lecture 33 – Word Sense Disambiguation: Overlap based Method; Supervised Method Unlimited
- Lecture 34 – Word Sense Disambiguation: Supervised and Unsupervised Methods Unlimited
- Lecture 35 – Word Sense Disambiguation: Semi-Supervised and Unsupervised Methods Unlimited
- Lecture 36 – Resource-Constrained WSD; Parsing Unlimited
- Lecture 37 – Parsing Unlimited
- Lecture 38 – Parsing Algorithm Unlimited
- Lecture 39 – Parsing Ambiguous Sentences; Probabilistic Parsing Unlimited
- Lecture 40 – Probabilistic Parsing Algorithms Unlimited
Instructor
