IT932
Course Name:
Intelligent Information Retrieval (IT932)
Programme:
Ph.D
Semester:
First
Credits (L-T-P):
4-0-0
Content:
Introduction, Basics Concepts, IR System Architecture; IR Models and Operations - Preprocessing, Bag of Words, Indexing, Boolean, Term Weighting, Vector-Space Retrieval, Probabilistic Models, Best Match Models, Latent Semantic Indexing, ; Experimental Evaluation of IR Systems; Document Representations; Query Operations and Languages; Relevance feedback and query expansion; Web Search and Link Analysis: Algorithms and evaluation; Structured Information Retrieval, Multimedia Information Retrieval; Recommender Systems; Information Extraction and Integration; Selected research papers on upcoming trends and open problems.
References:
C. D. Manning, P. Raghavan and H. Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.
Baeza-Yates & Ribeiro-Neto, Modern Information Retrieval, Pearson Education, 2010
Information Retrieval: Algorithms and Heuristics, by D. Grossman and O. Frieder, 2004
Information Retrieval: Implementing and Evaluating Search Engines, by S. Büttcher, C. Clarke, and G. Cormack., 2010
Korfhage Robert R, Information Storage and Retrieval, John Wiley & Sons, Inc, 1997.
Department:
Information Technology