Title :
Research of a Mining Algorithm Based on Markov Chain on WEB Page Access Sequence Features
Author :
Gang Liu ; Han Guo
Author_Institution :
Jilin Inst. of Archit. & Eng., Changchun, China
Abstract :
Web access to sequence data mining to help improve the quality of Web access, the sequence is a difficult problem in data mining, the prevalence of classic sequential algorithm and storage space overhead is too large defects. Web access sequence mining algorithm based on Markov chain can be found through less computation requests a web page. And for the design of the site, and achieved good results. Recognize that the most likely path through the site through the Web click-stream in order to predict the users will want to browse web pages, and accordingly to improve the design and construction of the site. Less computation to find the requested page, optimization of the hyperlink structure of the Web site.
Keywords :
Markov processes; Web sites; data mining; Markov chain; WEB page access sequence features; Web access sequence mining algorithm; Web click-stream; Web page browsing; Web site; classic sequential algorithm; hyperlink structure optimization; sequence data mining; storage space overhead; Data mining; Heuristic algorithms; Information filters; Markov processes; Web pages; Markov Chain; Mining Algorithm; Transfer Matrix; WEB;
Conference_Titel :
Information Technology and Applications (ITA), 2013 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-2876-7
DOI :
10.1109/ITA.2013.57