Proposing a New Method for Query Processing Adaption in DataBase
Mohammad-Reza Feizi-Derakhshi, Hasan Asil, Amir Asil
TL;DR
This paper introduces a multi-agent system that combines query processing optimization and adaptive features to enhance database query handling, utilizing a new algorithm and genetic algorithms for improved adaptability.
Contribution
It presents a novel multi-agent system integrating query optimization and adaptation, employing a new user requirement modeling algorithm and genetic algorithms.
Findings
Enhanced adaptation capability over classic algorithms
Effective modeling of users' long-term requirements
Improved query processing in dynamic environments
Abstract
This paper proposes a multi agent system by compiling two technologies, query processing optimization and agents which contains features of personalized queries and adaption with changing of requirements. This system uses a new algorithm based on modeling of users' long-term requirements and also GA to gather users' query data. Experimented Result shows more adaption capability for presented algorithm in comparison with classic algorithms.
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Taxonomy
TopicsData Management and Algorithms · Advanced Database Systems and Queries · Data Mining Algorithms and Applications