Name
Abstract | ||
|---|---|---|
The semantically associated network on the Web is a Semantic Link Network built by mining the associated relation between Web pages. The associated link from page A to page B indicates that users who have browsed page A is likely to also browse page B. This paper explores the statistical properties of the associated network on the Web. Web pages of a specific domain are automatically downloaded by a Web crawler to build an associated network. We analyze the associated network at different domain thresholds and classify the topology into three states, that is, the original state, the kernel state and the final state. A mathematical model is built to study the in-degree distribution, the out-degree distribution and the total-degree distribution for both the kernel state and the final state. By tuning the model parameters to reasonable values, we obtain the distinct power-law forms for the three degree distributions with exponents that agree well with the statistical data. The proposed model can not only describe the evolving processes of the associated network on the Web, but also provides theory basis for complex applications such as semantic community discovery, intelligent browsing and recommendation. Copyright © 2009 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1002/cpe.v22:7 | Concurrency and Computation: Practice and Experience |
Keywords | DocType | Volume |
Associated network,Degree distribution,Model,Power-law | Journal | 22 |
Issue | ISSN | Citations |
7 | 1532-0626 | 1 |
PageRank | References | Authors |
0.52 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xue Chen | 1 | 158 | 8.11 |
| Xiangfeng Luo | 2 | 1251 | 124.38 |
| Shunxiang Zhang | 3 | 125 | 18.93 |
| Zheng Xu | 4 | 352 | 19.51 |