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