Okapi BM25

Known as: Probabilistic relevance model 
In information retrieval, Okapi BM25 (BM stands for Best Matching) is a ranking function used by search engines to rank matching documents according… (More)
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Topic mentions per year

Topic mentions per year

1997-2016
05101519972016

Papers overview

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2013
2013
In this paper, we present some ideas about possible directions of a new interpretation of the Okapi BM25 ranking formula. In… (More)
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2012
2012
RÉSUMÉ Dans cette prise de position, nous nous intéressons au calcul de similarité (ou distances) entre textes, problématique pr… (More)
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2011
2011
We investigate the effect of feature weighting on document clustering, including a novel investigation of Okapi BM25 feature… (More)
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2011
2011
We reveal that the Okapi BM25 retrieval function tends to overly penalize very long documents. To address this problem, we… (More)
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Highly Cited
2010
Highly Cited
2010
We present and evaluate various content-based recommendation models that make use of user and item profiles defined in terms of… (More)
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Highly Cited
2007
Highly Cited
2007
In most existing retrieval models, documents are scored primarily based on various kinds of term statistics such as within… (More)
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Highly Cited
2006
Highly Cited
2006
We propose an integration of term proximity scoring into Okapi BM25. The relative retrieval effectiveness of our retrieval method… (More)
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Highly Cited
2004
Highly Cited
2004
All our submissions from the Microsoft Research Cambridge (MSRC) team this year continue to explore issues in IR from a… (More)
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Highly Cited
2003
Highly Cited
2003
Past research into text retrieval methods for the Web has been restricted by the lack of a test collection capable of supporting… (More)
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Highly Cited
2001
Highly Cited
2001
Query-expansion is an effective Relevance Feedback technique for improving performance in Information Retrieval. In general query… (More)
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