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A study of aboutness in information retrieval

A study of aboutness in information retrieval This paper addresses the notion of aboutness in information retrieval. First, an exposition is given on how aboutness relates to relevance—a fundamental notion in information retrieval. A short summary is given on how aboutness is defined in more prominent information retrieval models. A model-theoretic definition of aboutness is then analyzed in an abstract setting using so called information fields. These allows properties of aboutness to be expressed independent of any given information retrieval model. As a consequence, information retrieval models can be theoretically compared according to what aboutness postulates they support. The Boolean and Coordinate retrieval models are compared in this fashion. In addition to model-theoretic aboutness, preferential entailment and conditional probabilities are employed to define aboutness between primitive information carriers. The preferential entailment approach is based on a preference semantics derived from nonmonotonic logics. The nonmonotonic behaviour of aboutness under information composition is highlighted. Rules describing how aboutness may be preserved under composition are proposed. Finally, a term aboutness definition drawn from a network-based probabilistic framework is analyzed. Conclusions regarding the implied retrieval effectiveness are drawn. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

A study of aboutness in information retrieval

Artificial Intelligence Review , Volume 10 (6) – May 31, 2004

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References (42)

Publisher
Springer Journals
Copyright
Copyright
Subject
Computer Science; Artificial Intelligence; Computer Science, general
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/BF00130692
Publisher site
See Article on Publisher Site

Abstract

This paper addresses the notion of aboutness in information retrieval. First, an exposition is given on how aboutness relates to relevance—a fundamental notion in information retrieval. A short summary is given on how aboutness is defined in more prominent information retrieval models. A model-theoretic definition of aboutness is then analyzed in an abstract setting using so called information fields. These allows properties of aboutness to be expressed independent of any given information retrieval model. As a consequence, information retrieval models can be theoretically compared according to what aboutness postulates they support. The Boolean and Coordinate retrieval models are compared in this fashion. In addition to model-theoretic aboutness, preferential entailment and conditional probabilities are employed to define aboutness between primitive information carriers. The preferential entailment approach is based on a preference semantics derived from nonmonotonic logics. The nonmonotonic behaviour of aboutness under information composition is highlighted. Rules describing how aboutness may be preserved under composition are proposed. Finally, a term aboutness definition drawn from a network-based probabilistic framework is analyzed. Conclusions regarding the implied retrieval effectiveness are drawn.

Journal

Artificial Intelligence ReviewSpringer Journals

Published: May 31, 2004

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