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OKAPI BM25

Okapi BM25

Ranking function used by search engines

In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of

Okapi BM25

Okapi_BM25

BM25

Topics referred to by the same term

and made in the 1970s, it was seen in the late 1980s by photographers Okapi BM25, a ranking function in information retrieval This disambiguation page

BM25

Stephen Robertson (computer scientist)

British computer scientist

probabilistic information retrieval together with Karen Spärck Jones and the Okapi BM25 weighting model. Robertson was born in London, England,[citation needed]

Stephen Robertson (computer scientist)

Stephen_Robertson_(computer_scientist)

Okapi (disambiguation)

Topics referred to by the same term

Africa Okapi BM25, a ranking function used by search engines to rank matching documents according to their relevance to a given search query Okapi Framework

Okapi (disambiguation)

Okapi_(disambiguation)

Tf–idf

Estimate of the importance of a word in a document

Dirichlet allocation Latent semantic analysis Mutual information Noun phrase Okapi BM25 PageRank Vector space model Word count SMART Information Retrieval System

Tf–idf

Information retrieval

Finding information for an information need

Independence Model Probabilistic relevance model on which is based the okapi (BM25) relevance function Uncertain inference Language models Divergence-from-randomness

Information retrieval

Information_retrieval

Learned sparse retrieval

Document search algorithm

or vice versa. Some implementations of SPLADE have similar latency to Okapi BM25 lexical search while giving as good results as state-of-the-art neural

Learned sparse retrieval

Learned_sparse_retrieval

Cold start (recommender systems)

Potential problem in computer-based information systems

most of them are from the information retrieval domain like tf–idf, Okapi BM25, only a few have been developed specifically for recommenders. Hybrid

Cold start (recommender systems)

Cold_start_(recommender_systems)

Probabilistic relevance model

the same author. The best-known derivatives of this framework are the Okapi (BM25) weighting scheme and its multifield refinement, BM25F. Robertson, S

Probabilistic relevance model

Probabilistic_relevance_model

LGTE

Systems (ILPS). At the time, the tool was tested with success for the Okapi BM25 model, and a multinomial language model, but also includes divergence

LGTE