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JELIA 2014

Measuring Dissimilarity between Judgment Sets

Conference Paper Short Papers Artificial Intelligence · Knowledge Representation · Logic in Computer Science

Abstract

Abstract Distances and scores are widely used to measure (dis)similarity between objects of information such as preferences, belief sets, judgment sets, etc. Typically, measures are directly imported from information theory or topology, with little consideration for adequacy in the context of comparing logically related information. We propose a set of desirable properties for measures used to aggregate (logically related) judgments, and show which of the measures used for this purpose satisfy them.

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Keywords

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Context

Venue
European Conference on Logics in Artificial Intelligence
Archive span
2000-2023
Indexed papers
542
Paper id
692875240220864560