Department Events
Information Retrieval
- Introduction of IR and basic theories related to IR.
- Standard models of IR (Boolean, Vector-space, Probabilistic and Logical models).
- Understand the difficulty of representing and retrieving documents, images, speech, etc.
- Be familiar with various algorithms and systems and learning concepts about web search.
Motivation, Basic Concepts, Basic structure of search engine, Past and Future, The Retrieval Process, Web search and IR, Information Retrieval vs Data Retrieval , IR Vs. IE, Concept of relevance
Index Construction, Indexing techniques for textual information items, such as inverted indices, Document Preprocessing: tokenization, stemming and stop words. Pattern Matching.
Taxonomy of Information Retrieval Models, A Formal Characterization of IR Models.
Classic Information Retrieval: Basic Concepts, Boolean Model, Vector Model, Probabilistic Model, Brief Comparison of Classic Models
Language modeling. Probability ranking principle. Other commonly-used techniques include relevance feedback, pseudo relevance feedback, and query expansion and its Techniques.
Measures to compute similarity (Cosine, Jacquard), Retrieval performance evaluation: Recall and Precision, NDCG.
Web structure & Characteristics, Web Crawling and Indexes, Link Analysis, Introduction to IR based on Semantics, Ontologies.
- C.D. Manning, P. Raghavan, H. Schütze, “Introduction to Information Retrieval”, Cambridge UP, 2008.
- D.A. Grossman, O. Frieder, “Information Retrieval: Algorithms and Heuristics”, Springer, 2004.
- G. Kowalski, M.T. Maybury. “Information Storage and Retrieval Systems”, Springer, 2005.
- C.J. van Risjbergen. “The Geometry of Information Retrieval” Cambridge UP, 2004.
- B. Croft, D. Metzler, T. Strohman, “Information Retrieval in Practice” Pearson Education, 2009.
- R. Baeza-Yates, B. Ribeiro-Neto, “ Modern Information Retrieval” . Addison-Wesley, 1999
