Title: Answering conjunctive fuzzy query using views: efficient algorithm to return the best k-tuples pervasive healthcare application

Authors: Wissem Labbadi; Jalel Akaichi

Addresses: Department of Computer Science, Institut Supérieur de Gestion, University of Tunis, Le Bardo, 2000, Tunisia ' Department of Information Systems, College of Computer Science, King Khaled University, Abha, Saudi Arabia

Abstract: In this work, we consider the problem of efficiently finding the top-K answers for a conjunctive fuzzy query used to express users' preferences in a non-crisped way, from the top-N conjunctive query rewritings. We propose an algorithm for finding the top-N query rewritings of a medical conjunctive fuzzy query using a set of conjunctive crisp views. At the best of our knowledge, this algorithm is the first to generate, without computing all possible rewritings, the N best ones ordered according to their satisfaction degrees and that are likely to return the best K-answers for the user fuzzy query. The relevance of a query rewriting is estimated using a second algorithm proposed to estimate, through the histograms maintained to approximate the distribution of set of values returned by the rewriting and to which fuzzy predicates are related, the pertinence of a conjunctive fuzzy query rewriting rather than accessing the database relations.

Keywords: pervasive computing; medical conjunctive fuzzy queries; top-N query rewritings; top-K tuples; query satisfaction; views; pervasive healthcare; user preferences; user queries.

DOI: 10.1504/IJMEI.2015.072321

International Journal of Medical Engineering and Informatics, 2015 Vol.7 No.4, pp.293 - 312

Received: 04 Mar 2014
Accepted: 06 Oct 2014
Published online: 09 Oct 2015 *

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