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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.
Artificial Intelligence Review – Springer Journals
Published: May 31, 2004
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