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A flexible approach to evaluating soft conditions with unequal preferences in fuzzy databases
Author(s) -
Bordogna Gloria,
Pasi Gabriella
Publication year - 2007
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20223
Subject(s) - parameterized complexity , fuzzy logic , news aggregator , function (biology) , computer science , measure (data warehouse) , semantics (computer science) , meaning (existential) , soft computing , similarity (geometry) , database , mathematics , data mining , artificial intelligence , algorithm , programming language , psychology , evolutionary biology , psychotherapist , biology , operating system , image (mathematics)
A flexible model for evaluating soft query with unequal preferences in fuzzy databases is proposed. We assume that conditions with unequal preferences have an exclusive meaning like in the request “find a holiday accommodation such that big apartments are preferred to high rating hotels.” In this case it is assumed that the aggregator of the soft conditions is an implicit OR. Conversely, conditions with unequal importance have an inclusive meaning, like in the query “find a house to rent that is cheap (most important), big (important), new (fairly important).” In this case the implicit aggregator is an AND. What we propose in this article is to model preferences as modifiers of the semantics of the evaluation function of the conditions. Because the soft conditions are aggregated by an OR, the more a soft condition is preferred, the more its evaluation function tolerates a greater undersatisfaction of the soft condition. The proposed approach is formalized by considering two alternative semantics of the evaluation function: the first semantics defines the evaluation function by means of a generalized fuzzy inclusion measure, and the second one as a generalized similarity measure. These functions are parameterized so that their modification is simply achieved by tuning the functions' parameters. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 665–689, 2007.