Abstract
The fuzzy queries represent a solution to enhance the bipolar behavior of the classical querying in relational databases (RDB) in order to deal with the empty answer problem. This problem is defined by the execution of queries that do not return any answer. So, the fuzzy queries provide the user with some alternative data when there is no response satisfies his or her query. The aim of this paper is to present a solution to the empty answer problem based on cooperative answers and the proximity measure for improving fuzzy querying in RDB. The proximity measure is based on the use of the Hausdorff distance as a similarity measure between a failing query (query with the empty answer) and some other successful ones whose answers are not empty. Our idea is to assign the closest query’s answers to the one that failed as cooperative answers. We propose four gradual operators based on usual ones between predicates for enhancing fuzzy queries. The experimental results show that our approach is a promising way for improving fuzzy queries in relational databases.
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Aggoune, A. (2020). A Fuzzy Querying Using Cooperative Answers and Proximity Measure. In: Bouhlel, M., Rovetta, S. (eds) Proceedings of the 8th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18), Vol.1. SETIT 2018. Smart Innovation, Systems and Technologies, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-030-21005-2_4
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