lecture9-queryexpansion-handout-6-per

but some dont because its hard to explain to average

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Unformatted text preview: ec*on (set of documents minus those assessed relevant)   Measures usually then lower than for original query   But a more realis*c evalua*on   Rela*ve performance can be validly compared Introduc)on to Informa)on Retrieval Sec. 9.1.5 Evalua*on of relevance feedback   Second method – assess only the docs not rated by the user in the first round   Could make relevance feedback look worse than it really is   Can s*ll assess rela*ve performance of algorithms   Most sa*sfactory – use two collec*ons each with their own relevance assessments   q0 and user feedback from first collec*on   qm run on second collec*on and measured   Empirically, one round of relevance feedback is oken very useful. Two rounds is some*mes marginally useful. 6 Introduc)on to Informa)on Retrieval Sec. 9.1.3 Evalua*on: Caveat Introduc)on to Informa)on Retrieval Relevance Feedback on the Web   True evalua*on of usefulness must compare to other methods taking the same amount of *me.   Alterna*ve to relevance feedback: User revises and resubmits query.   Users may prefer revision/resubmission to having to judge relevance of documents.   There is no clear evidence that relevance feedback is the best use of the user s *me. Introduc)on to Informa)on Retrieval S ec. 9.1.4 Sec. 9.1.4   Some search engines offer a similar/related pages feature (this is a trivial form of relevance feedback)   Google (link ­based)   Altavista   Stanford WebBase α/β/γ ??   But some don’t because it’s hard to explain to average user:   Alltheweb   bing   Yahoo   Excite ini*ally had true relevance feedback, but abandoned it due to lack of use. Introduc)on to Informa)on Retrieval Sec. 9.1.6 Excite Relevance Feedback Pseudo relevance feedback Spink et al. 2000  ...
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