Stanford CS 124 - Introductionon to Information Retrieval (93 pages)

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Introductionon to Information Retrieval



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Introductionon to Information Retrieval

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Pages:
93
School:
Stanford University
Course:
Cs 124 - From Languages to Information

Unformatted text preview:

Introduc on to Informa on Retrieval Introduc on to Informa on Retrieval Introducing ranked retrieval Introduc on to Informa on Retrieval Ch 6 Ranked retrieval Thus far our queries have all been Boolean Documents either match or don t Good for expert users with precise understanding of their needs and the collec on Also good for applica ons Applica ons can easily consume 1000s of results Not good for the majority of users Most users incapable of wri ng Boolean queries or they are but they think it s too much work Most users don t want to wade through 1000s of results This is par cularly true of web search Introduc on to Informa on Retrieval Problem with Boolean search feast or famine Ch 6 Boolean queries oNen result in either too few 0 or too many 1000s results Query 1 standard user dlink 650 200 000 hits Query 2 standard user dlink 650 no card found 0 hits It takes a lot of skill to come up with a query that produces a manageable number of hits AND gives too few OR gives too many Introduc on to Informa on Retrieval Ranked retrieval models Rather than a set of documents sa sfying a query expression in ranked retrieval models the system returns an ordering over the top documents in the collec on with respect to a query Free text queries Rather than a query language of operators and expressions the user s query is just one or more words in a human language In principle there are two separate choices here but in prac ce ranked retrieval models have normally been associated with free text queries and vice versa 4 Introduc on to Informa on Retrieval Feast or famine not a problem in ranked retrieval Ch 6 When a system produces a ranked result set large result sets are not an issue Indeed the size of the result set is not an issue We just show the top k 10 results We don t overwhelm the user Premise the ranking algorithm works Introduc on to Informa on Retrieval Ch 6 Scoring as the basis of ranked retrieval We wish to return in order the documents most likely to be useful



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