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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lei Xiang Xin Meng |
| Copyright Year | 2009 |
| Abstract | 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. |
| Starting Page | 595 |
| Ending Page | 599 |
| File Size | 738724 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769538044 |
| DOI | 10.1109/ICICTA.2009.378 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-10-10 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Crawlers knowledge discovery mining Data mining Uniform resource locators Content addressable storage Space technology Web pages Search engines Software Internet Web sites information process |
| Content Type | Text |
| Resource Type | Article |
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