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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yi Zhang Lei Zhang Yan Zhang Xiaoming Li |
| Copyright Year | 2006 |
| Description | Author affiliation: Peking University, China (Yi Zhang; Lei Zhang; Yan Zhang; Xiaoming Li) |
| Abstract | Link analysis has been widely used to evaluate the importance of web pages. PageRank, the most famous link analysis algorithm, offers an effective way to rank the pages. However, the algorithm ignores three facts. First, nowadays the way that users retrieve information is quite different from the previous way when web search engine was not extensively used. Second, inter-site links and intra-site links should not be treated equally. A link from a different site is more important for a page than that within the same site. Third, most users start their browsing from a homepage, which should be given more weight than other pages. In this paper, we propose a novel ranking algorithm called XRank as a solution to these problems. Experimental results on the CWT100g show that our XRank algorithm outperforms other famous ranking algorithms, including PageRank and Two-Layer PageRank, especially on sites recommendation and web spam avoidance. |
| Starting Page | 36 |
| Ending Page | 36 |
| File Size | 160332 |
| Page Count | 1 |
| File Format | |
| ISBN | 076952687X |
| DOI | 10.1109/CIT.2006.198 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-09-20 |
| Publisher Place | Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Computer science Continuous wavelet transforms Laboratories Web pages Machine learning Search engines Information retrieval Probability distribution Web search |
| Content Type | Text |
| Resource Type | Article |
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