DocumentCode :
2255878
Title :
Research on client behavior pattern recognition system based on Web log mining
Author :
Gao, Wen-Hai
Author_Institution :
Coll. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Volume :
1
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
466
Lastpage :
470
Abstract :
With the explosive growth of data available on the World Wide Web, the sheer volume of traffic is kept on the enterprise´s Web site. Discovery and analysis of useful information from the World Wide Web becomes a practical necessary. Web Log Mining is the application of Data Mining techniques to discover Client behavior patterns from Web data in order to understand and serve the needs of Web. In the article we will introduce the method how to use data mining technique to excavate the client behavior pattern from Web log file, and play an emphasis on analyzing client behavior pattern recognition system and its application, so as to help enterprises obtain client information conveniently and automatically.
Keywords :
Internet; behavioural sciences computing; business data processing; consumer behaviour; customer relationship management; data mining; pattern recognition; Web log mining; World Wide Web; client behavior pattern; client behavior pattern recognition system; data mining technique; enterprise Web site; Analytical models; Business; Data mining; Data models; Internet; Web sites; Client behavior patterns; Data mining; Electronic business; Web log mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
Type :
conf
DOI :
10.1109/ICMLC.2010.5581016
Filename :
5581016
Link To Document :
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