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A New Approach For Top-k Flexible Queries In Large Database Using The Knowledge Discovered

Authors:
Amel Grissa touzi
Habib Ounalli

Keywords: Top-k queries; KDD; Data minig; FCA; Fuzzy logic.

Abstract:
In this paper, we propose our contribution to support top-k flexible query in large DB. Generally, the current top-k query processing techniques focus on Boolean queries, and cannot be applied to the large DB seen the gigantic number of data. Our approach proposes to uses the generated knowledge result of an algorithm for Knowledge Discovery in Database (KDD). It consists of two steps: 1) Extraction of Knowledge by applying a new approach for KDD through the fusion of conceptual clustering, fuzzy logic and formal concept analysis, and 2) generation efficient answers to top-k flexible queries using the generated knowledge in the first step. We prove that this approach is optimum sight that the evaluation of the query is not done on the set of starting data which are enormous but rather by using the set of knowledge on these data; what is to our opinion one of the principal’s goal of KDD approaches.

Pages: 103 to 111

Copyright: Copyright (c) IARIA, 2012

Publication date: February 29, 2012

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-185-4

Location: Saint Gilles, Reunion

Dates: from February 29, 2012 to March 5, 2012