DocumentCode :
2337215
Title :
Research on the knowledge rule mining method for the evaluation of library website based on genetic algorithm
Author :
Ping, Wang ; Tai-shan, Yan ; Qun, Chen
Author_Institution :
Libr., Hunan Inst. of Sci. & Technol., Yueyang, China
fYear :
2012
fDate :
3-5 June 2012
Firstpage :
369
Lastpage :
372
Abstract :
Evaluation of library website depends on the knowledge rules to a large extent. In this study, the evaluation index system of library website is established and the representation method of knowledge rule is analyzed firstly. Then, a knowledge rule mining method for the evaluation of library website based on an improved genetic algorithm is proposed. In the algorithm, selection operator, help operator, crossover operator and mutation operator are used to generate new knowledge rules. Knowledge rules are evaluated by their accuracy, coverage and reliability. Experimental results show that this knowledge rule mining method is feasible and valid. It will be helpful for us to evaluate the library website fairly and objectively.
Keywords :
Web sites; data mining; genetic algorithms; knowledge representation; library automation; reliability; crossover operator; evaluation index system; genetic algorithm; help operator; knowledge representation; knowledge rule mining method; library Website evaluation; mutation operator; reliability; selection operator; Encoding; Genetic algorithms; Genetics; Indexes; Knowledge engineering; Libraries; Robots; Evaluation of library website; Genetic algorithm; Knowledge rule base; Knowledge rule mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
Type :
conf
DOI :
10.1109/ISRA.2012.6219201
Filename :
6219201
Link To Document :
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