Level-Biased statistics in the hierarchical structure of the web

Authors:
Guang Feng;Tie-Yan Liu;Xu-Dong Zhang;Wei-Ying Ma
Affiliations:
Microsoft Research Asia, Beijing, P.R. China;MSPLAB, Department of Electronic Engineering, Tsinghua University, Beijing, P.R. China;Microsoft Research Asia, Beijing, P.R. China;MSPLAB, Department of Electronic Engineering, Tsinghua University, Beijing, P.R. China
Venue:
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Year:
2006

Citing 3
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Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
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APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development

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Abstract

In the literature of web search and mining, researchers used to consider the World Wide Web as a flat network, in which each page as well as each hyperlink is treated identically. However, it is the common knowledge that the Web is organized with a natural hierarchical structure according to the URLs of pages. Exploring the hierarchical structure, we found several level-biased characteristics of the Web. First, the distribution of pages over levels has a spindle shape. Second, the average indegree in each level decreases sharply when the level goes down. Third, although the indegree distributions in deeper levels obey the same power law with the global indegree distribution, the top levels show a quite different statistical characteristic. We believe that these new discoveries might be essential to the Web, and by taking use of them, the current web search and mining technologies could be improved and thus better services to the web users could be provided.