Extending a web browser with client-side mining

Authors:
Hongjun Lu;Qiong Luo;Yeuk Kiu Shun
Affiliations:
Hong Kong University of Science and Technology, Department of Computer Science, Kowloon, Hong Kong, China;Hong Kong University of Science and Technology, Department of Computer Science, Kowloon, Hong Kong, China;Hong Kong University of Science and Technology, Department of Computer Science, Kowloon, Hong Kong, China
Venue:
APWeb'03 Proceedings of the 5th Asia-Pacific web conference on Web technologies and applications
Year:
2003

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Abstract

We present WBext (Web Browser extended), a web browser extended with client-side mining capabilities. WBext learns sophisticated user interests and browsing habits by tailoring and integrating data mining techniques including association rules mining, clustering, and text mining, to suit the web browser environment. Upon activation, it automatically expands user searches, re-ranks and returns expanded search results in a separate window, in addition to returning the original search results in the main window. When a user is viewing a page containing a large number of links, WBext is able to recommend a few links from those that are highly relevant to the user, considering both the user's interests and browsing habits. Our initial results show that WBext performs as fast as a common browser and that it greatly improves individual users' search and browsing experience.