64 introducon to informaon retrieval evidence

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Unformatted text preview: Issues for biword indexes §༊  False posi*ves, as noted before §༊  Index blowup due to bigger dic*onary §༊  Infeasible for more than biwords, big even for them §༊  Biword indexes are not the standard solu*on (for all biwords) but can be part of a compound strategy Introduc)on to Informa)on Retrieval Sec. 2.4.2 Solu*on 2: Posi*onal indexes §༊  In the pos*ngs, store, for each term the posi*on(s) in which tokens of it appear: <term, number of docs containing term; doc1: posi*on1, posi*on2 … ; doc2: posi*on1, posi*on2 … ; etc.> Introduc)on to Informa)on Retrieval S ec. 2.4.2 Posi*onal index example <be: 993427; 1: 7, 18, 33, 72, 86, 231; 2: 3, 149; 4: 17, 191, 291, 430, 434; 5: 363, 367, …> Which of docs 1,2,4,5 could contain “to be or not to be”? §༊  For phrase queries, we use a merge algorithm recursively at the document level §༊ ...
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This document was uploaded on 02/14/2014.

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