NDLI: Utilize Fuzzy Data Mining to Find the Travel Pattern of Browsers

Content Provider	IEEE Xplore Digital Library
Author	Qingzhan Chen Han Jianghong Wenxiu He Keji Mao Yungang Lai
Copyright Year	2005
Description	Author affiliation: Hefei Univ. of Technol. (Qingzhan Chen; Han Jianghong)
Abstract	With the traveling records of browsers, one can analyze the preference of pages, further understand the demands of consumers, and promote the advertising and marketing. In this study, we use maximum forward reference (MFR) algorithm to find the travel pattern of browsers from Web logs. Simultaneously, experts are asked to evaluate the fuzzy importance weightings for different Webs. At last, we employ fuzzy data mining technique that combines Apriori algorithm with fuzzy weights to determine the association rules. From the yielded association rules, one can be accurately aware of the information consumers need and which Webs they prefer. This is important to governmental institutions and enterprises. Enterprises can find the commercial opportunities and improve the design of Webs by means of this study. Governmental institutions can realize the needs of people from the obtained association rules, make the promotion of policy more efficiently, and provide better service quality
Sponsorship	Univ. of Aizu, Japan Nat. Natural Sci. Found. China Fudan GrandHorizon Inf. Technol., Inc. China Hewlett-Packard Co., Ltd
Starting Page	228
Ending Page	232
File Size	185194
Page Count	5
File Format	PDF
ISBN	076952432X
DOI	10.1109/CIT.2005.197
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Web page design Web design Feedback Web pages Data Mining Maximum Forward Reference Fuzzy set theory Data mining Association rules Advertising Fuzzy systems
Content Type	Text
Resource Type	Article

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