By Topic

A Data Mining Approach to Topic-Specific Web Resource Discovery

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Lei Xiang ; Center for Space Sci. & Appl. Res., Chinese Acad. of Sci., Beijing, China ; Xin Meng

The rapid growth of World Wide Web in recent years has made it important to carry out resource discovery Topic-specific web crawler collects relevant web pages of interested topics from the Internet, there are many relevant researches focusing on topic-specific crawling. However few works detail the topic-specific crawling with the user interests. In this paper, we present a new user interests model to optimize the performance of the topic-specific crawler. The crawler can learn from the previous experience to improve the proportion of the number of relevant pages and the number of the whole pages by using the user information, which is collected by data mining approach.

Published in:

Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on  (Volume:2 )

Date of Conference:

10-11 Oct. 2009