Measuring the likelihood property of scoring functions in general retrieval models
- Bache, Richard Dept. Computer and Information Science, University of
- Strathclyde, Glasgow, Scotland
- Baillie, Mark Dept. Computer and Information Science, University of Strathclyde,
- Glasgow, Scotland
- Crestani, Fabio Facoltà di scienze informatiche, Università della Svizzera italiana,
- Svizzera
-
2007
Published in:
- Journal of the American society for information science and technology. - Wiley Periodicals. - 2009, vol. 60, no. 6, p. 1294-1297
English
Although retrieval systems based on probabilistic models will rank the objects (e.g. documents) being retrieved according to the probability of some matching criterion (e.g. relevance) they rarely yield an actual probability and the scoring function is interpreted to be purely ordinal within a given retrieval task. In this paper it is shown that some scoring functions possess the likelihood property, which means that the scoring function indicates the likelihood of matching when compared to other retrieval tasks which is potentially more useful than pure tanking although it cannot be interpreted as an actual probability. This property can be detected by using two modified effectiveness measure, entire precision and entire recall. Empirical evidence is offered to show the existence of this property both for traditional document retrieval and for analysis of crime data where suspects of an unsolved crime are ranked according to probability of culpability.
- Language
-
- English
- Classification
- Computer science and technology
- License
- License undefined
- Identifiers
-
- RERO DOC 11941
- DOI 10.1002/asi.21048
- ARK ark:/12658/srd1318120
- Persistent URL
- https://n2t.net/ark:/12658/srd1318120
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