Information Extraction and Retrieval - IIIT Hyderabad

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Boolean Model • Simple model based on set theory • Queries specified as Boolean expressions – precise semantics – neat formalism – q = ka ∧ (kb ∨ ¬kc) • Terms are either present or absent. Thus, w ij ε {0,1} 22
Drawbacks of the Boolean Model • <strong>Retrieval</strong> based on binary decision criteria with no notion of partial matching • No ranking of the documents is provided (absence of a grading scale) • <strong>Information</strong> need has to be translated into a Boolean expression which most users find awkward • The Boolean queries formulated by the users are most often too simplistic • Frequently returns either too few or too many documents in response to a user query 23
Page 1 and 2: IR Systems (Note: Many slides from
Page 3 and 4: Approaches to IR Two types of
Page 5 and 6: Typical IR Task Given: Find: A
Page 7 and 8: Web Search System Web Spider Docume
Page 9 and 10: Keyword Search Simplest notion of
Page 11 and 12: Relevant items are similar Much of
Page 13 and 14: How effective is IR? Anecdotal e
Page 15 and 16: Intelligent IR Taking into account
Page 17 and 18: IR System Components Text Operati
Page 19 and 20: IR Models Set Theoretic Classic Mod
Page 21: Classic IR Models - Basic Concepts
Page 25 and 26: Vector-based Model • Define: - w
Page 27 and 28: Vector Based Model • Sim(q,d j )
Page 29 and 30: Probabilistic Model • An initial
Page 31: 31 Thank You - Questions? Vasudeva

Information Extraction and Retrieval - IIIT Hyderabad

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