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lecture6-tfidf-handout-6-per

Query 1 standard user dlink 650 200000 hits query

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Unformatted text preview: . Introduc)on to Informa)on Retrieval Problem with Boolean search: feast or famine Ch. 6   Boolean queries o]en 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, the system returns an ordering over the (top) documents in the collec*on for 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 has normally been associated with free text queries and vice versa 6 1 Introduc)on to Informa)on Retrieval Feast or famine: not a problem in ranked retrieval Ch. 6   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 Ch. 6 Scoring as the basis of ranked retrieval   When a system produces a ranked result set, large result sets are not an issue Introduc)on to Informa)on Retrieval Introduc)on to Informa)on Retrieval Ch. 6   We wish to return in order the documents most likely to be useful to the searcher   How can we rank ­order the documents in the collec*on with respect to a query?   Assign a score – say in [0, 1] – to each document   This score...
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