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