TY - GEN
T1 - Level-biased statistics in the hierarchical structure of the Web
AU - Feng, Guang
AU - Liu, Tie-Yan
AU - Zhang, Xu-Dong
AU - Ma, Wei-Ying
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2006
Y1 - 2006
N2 - 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. © Springer-Verlag Berlin Heidelberg 2006.
AB - 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. © Springer-Verlag Berlin Heidelberg 2006.
UR - https://www.scopus.com/pages/publications/33745833989
UR - https://www.scopus.com/pages/publications/33745833989#tab=impact
U2 - 10.1007/11731139_37
DO - 10.1007/11731139_37
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 3540332065
SN - 9783540332060
VL - 3918 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 313
EP - 322
BT - Advances in Knowledge Discovery and Data Mining - 10th Pacific-Asia Conference, PAKDD 2006, Proceedings
PB - Springer Verlag
T2 - 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006
Y2 - 9 April 2006 through 12 April 2006
ER -