From User Requirements to Querying of Fuzzy Summaries

From User Requirements to Querying of Fuzzy Summaries

Ines Benali Sougui (Ecole Nationale d'Ingénieurs de Tunis, Université de Tunis El Manar, Tunis, Tunisia), Minyar Sassi Hidri (Ecole Nationale d'Ingénieurs de Tunis, Université de Tunis El Manar, Tunis, Tunisia) and Amel Grissa Touzi (Ecole Nationale d'Ingénieurs de Tunis, Université de Tunis El Manar, Tunis, Tunisia)
DOI: 10.4018/ijssmet.2014010105
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Abstract

With the huge amount and the evolution of fuzzy data, the necessity to work with synthetic views became a challenge for many databases (DB) community researchers. Data summarization techniques are now considered as accurate tools to handle huge DB, in particular when precise data are not needed. Formal approaches have been proposed making possible the generation of an hierarchy of summaries from DB. The challenges arise on the question of how querying these fuzzy views according user requirements. In this work, we propose to handle with these challenges by query repairing and substitution. Two process were studied, the first process is used by modifying query while using the best fuzzy summaries which have the most near answers. The second one is applied to generate all substitution queries over the fuzzy summaries' hierarchy. This would be not only expensive but also unjustified for the part of the search hierarchy nodes.
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Preliminaries

In this section, we present the basic concepts of FDB, Fuzzy attributes in GEFRED model and the theoretical foundations of fuzzy FCA.

Fuzzy Databases (FDB)

In this section, we present the basic concepts of FDB. A FDB is an extension of the relational database. This extension introduces fuzzy predicates under shapes of linguistic expressions that, at the time of a flexible querying, permits to have a range of answers (each one with a membership degree) in order to offer to the user all intermediate variations between the completely satisfactory answers and those completely dissatisfactory (Bosc et al., 1998). The FRDB models are considered in a very simple shape and consist in adding a degree, usually in the interval [0,1], to every tuple. It allows maintaining the homogeneity of the data in DB. The main models are those of PradeTestemale (Prade et al., 1987), Umano-Fukami (Umano et al., 1980), Buckles-Petry (Buckles et al., 1982), ZemankovaKaendel (Zemankova-Leech, 1985) and GEFRED of Medina et al. (Medina et al., 1994). This last model constitutes an eclectic synthesis of the various models published so far with the aim of dealing with the problem of representation and treatment of fuzzy information by using relational DB.

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