Title :
Using genetic algorithm for avoiding redundant matched substring within a web based join framework
Author :
Thenmozhi, R. ; Anandajothi, M.
Author_Institution :
Comput. Sci. Dept., Pondicherry Univ., Pondicherry, India
Abstract :
The popular AML (Approximate Membership Localization) is the process of delivers a full coverage to the true matched substrings from single given document, but redundancies cause a low efficiency of AML process and deteriorate the performance of the real world applications using the extracted substrings. Though the results of AML are proved to be good over Approximate Membership Extraction (AME), redundancy is still occurring and the results of AML are much closer to AME. In this paper, to refine the results of AML we moved to the genetic algorithm for better efficiency and to avoid the redundancy completely.
Keywords :
Internet; data mining; genetic algorithms; AME; AML; Web based join framework; approximate membership extraction; approximate membership localization; genetic algorithm; redundant matched substring; Algorithm design and analysis; Data mining; Databases; Dictionaries; Educational institutions; Genetic algorithms; Redundancy; Web-based join; approximate membership localization (AML); exact matching; genetic algorithm; redundancy;
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3835-3
DOI :
10.1109/ICICES.2014.7033948
