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Discover Computing
Erschienen in: Discover Computing 3/2008

01.06.2008

A probability ranking principle for interactive information retrieval

verfasst von: Norbert Fuhr

Erschienen in: Discover Computing | Ausgabe 3/2008

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Abstract

The classical Probability Ranking Principle (PRP) forms the theoretical basis for probabilistic Information Retrieval (IR) models, which are dominating IR theory since about 20 years. However, the assumptions underlying the PRP often do not hold, and its view is too narrow for interactive information retrieval (IIR). In this article, a new theoretical framework for interactive retrieval is proposed: The basic idea is that during IIR, a user moves between situations. In each situation, the system presents to the user a list of choices, about which s/he has to decide, and the first positive decision moves the user to a new situation. Each choice is associated with a number of cost and probability parameters. Based on these parameters, an optimum ordering of the choices can the derived—the PRP for IIR. The relationship of this rule to the classical PRP is described, and issues of further research are pointed out.
Vorheriger Artikel Document keyphrases as subject metadata: incorporating document key concepts in search results

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Fußnoten
1
The columns headed \(n_{q^\prime}\) and \(\varrho_{ij}\) are explained in Sect. 6.
 
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Metadaten
Titel
A probability ranking principle for interactive information retrieval
verfasst von
Norbert Fuhr
Publikationsdatum
01.06.2008
Verlag
Springer Netherlands
Erschienen in
Discover Computing / Ausgabe 3/2008
Print ISSN: 2948-2984
Elektronische ISSN: 2948-2992
DOI
https://doi.org/10.1007/s10791-008-9045-0