Document (#43640)

Author

Dang, E.K.F.
Luk, R.W.P.
Allan, J.

Title

¬A retrieval model family based on the probability ranking principle for ad hoc retrieval

Source

Journal of the Association for Information Science and Technology. 73(2022) no.8, S.1140-1154

Year

2022

Abstract

Many successful retrieval models are derived based on or conform to the probability ranking principle (PRP). We present a new derivation of a document ranking function given by the probability of relevance of a document, conforming to the PRP. Our formulation yields a family of retrieval models, called probabilistic binary relevance (PBR) models, with various instantiations obtained by different probability estimations. By extensive experiments on a range of TREC collections, improvement of the PBR models over some established baselines with statistical significance is observed, especially in the large Clueweb09 Cat-B collection.

Content

https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24619.

Theme

Retrievalalgorithmen

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4. Savoy, J.: ¬A new probabilistic scheme for information retrieval in hypertext (1995) 0.21

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5. Trotman, A.: Choosing document structure weights (2005) 0.20

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