'Information Retrieval' is an elective course offered in M. Tech. in Computer Science and Engineering at School of Engineering, Amrita Vishwa Vidyapeetham.
Introduction to IR: Space Retrieval Models - Ranked Retrieval - Text Similarity Metrics - Tokenizing- stemming-Evaluations on benchmark text collections - Components of an information retrieval system. Indexing for IR: Inverted Indices - Postings lists - Optimizing indices with skip lists - Proximity and phrase queries - Positional indices - Dictionaries and tolerant retrieval - Dictionary data structures - Wild-card queries- n-gram indices - Spelling correction and synonyms - Edit distance - Index construction - Dynamic indexing - Distributed indexing - real-world issues. Relevance in IR: Parametric or fielded search - Document zones - Vector space retrieval model - tf.idf weighting - queries as vectors - Computing scores in a complete search system - Efficient scoring and ranking - Evaluation in information retrieval : User happiness- Creating test collections: kappa measure-interjudge agreement - Relevance feedback and query expansion: Query expansion - Automatic thesaurus generation - Sense-based retrieval -. Document Classification and Clustering: Introduction to text classification -Latent Semantic Indexing.
TEXTBOOKS/REFERENCES
- C. Manning, P. Raghavan, and H. Schütze, “Introduction to Information Retrieval”, Cambridge University Press, 2008.
- R. Baeza-Yates and B. Ribeiro Neto,“Modern Information Retrieval: The Concepts and Technology behind Search”, Second Edition, Addison Wesley, 2011.
- David A. Grossman and Ophir Frieder “Information Retrieval: Algorithms and Heuristics”, Second Edition, Springer 2004.
