It shows some theoretical results for understanding the distribution of the score in the Web according to PageRank. Seven golden rules for building good pages are presented.
It proposes a new weighted HITS-based method that assigns appropriate weights to in-links of root documents and combines content analysis with HITS-based algorithms.
"Random Surfer" model extension. At each step of traversal of the Web graph, the surfer can jump to a random node or follow a hyperlink or follow a back-link (a hyperlink in the inverse direction) or stay in the same node.
Taher H. Haveliwala's paper for the 11th International World Wide Web Conference explains that Google proposes to make PageRank reflect importance with respect to a particular topic.
By Soumen Chakrabarti, Mukul M. Joshi, Kunal Punera and David M. Pennock, IIT Bombay and NEC Research Institute. In: Proceedings of the 11th international conference on World Wide Web, 2002. Many studies on the Web graph concentrate on the graph struc...
T. Haveliwala proposes bringing topical information into PageRank calculation, using pages listed in the ODP. In: Proceedings of the Eleventh International World Wide Web Conference, May 2002.