Title :
Research on web association rules mining structure with genetic algorithm
Author :
Tang, Ya-ling ; Qin, Feng
Author_Institution :
Sch. of Comput., AnHui Univ. of Technol., Maanshan, China
Abstract :
Association rules are import basis of describing Web users´ behavior characteristic. Traditional algorithms of Web association rules mining, based on statistics, usually pays attention to the analysis on existing data,they can´t offer effective predictive means and optimizing measure and can not find out the latent and possible rules. This paper presents a kind of system of the Web association rules mining based on genetic algorithm, which proves by experiment that it can mend the traditional Web association mining method of lack of foreseeing in latency. And it puts forward a new ideal of Web association rules mining.
Keywords :
Internet; data mining; genetic algorithms; statistical analysis; Web association rules mining structure; Web users behavior; genetic algorithm; statistics; Algorithm design and analysis; Association rules; Biological cells; Encoding; Genetics; Web sites; Data Mining; Genetic Algorithm; Increment Mining; Machine Learning; Web Association Rules;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5553906