文章基本信息

标题：Memory Optimization Using Genetic Algorithm of Relational Keyword Search Techniques
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作者：A.Ravichandiran ; A.Vijayan ; K.Ravikumar 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：4
DOI：10.15680/ijircce.2015.0304080
出版社：S&S Publications
摘要：Currently the relational keyword based searches techniques consider the large number of data’s toprovide efficient result while the user searching. There is an issue of limited memory hence there is a need of theimplementation of the novel techniques/ algorithm. To improve the search technique process by optimizing the queryfrom that has to attain the memory optimization with the help of the genetic algorithm. Here the genetic algorithmplays the major role to select the optimized query to execute in the final result execution process based on the usergiven query. Here the process is executed in the dynamic manner which is considered as the real time scenario in thathave to execute the whole process as the dynamic based on the user given query. The proposed system called MOGA.It means Memory Optimization with Genetic Algorithm. Here the memory is optimized based on the user given queryto search the particular term. Then the User search goal is attained by applying the efficient clustering technique calledFuzzy C Means Clustering on the Clicked URL Data. The performance will be executed in terms of the spaceconsumption and the time complexity of the searching process. In the past decade, extending the keyword searchparadigm to relational data has been an active area of research within the database and information retrieval (IR)community. A large number of approaches have been proposed and implemented, but despite numerous publications,there remains a severe lack of standardization for system evaluations
关键词：Keyword search; relational database; information retrieval; empirical evaluation