Utility analysis for topically biased PageRank

ABSTRACT

PageRank is known to be an efficient metric for computing general document importance in the Web. While commonly used as a one-size-fits-all measure, the ability to produce topically biased ranks has not yet been fully explored in detail. In particular, it was still unclear to what granularity of "topic" the computation of biased page ranks makes sense. In this paper we present the results of a thorough quantitative and qualitative analysis of biasing PageRank on Open Directory categories. We show that the MAP quality of Biased PageRank generally increases with the ODP level up to a certain point, thus sustaining the usage of more specialized categories to bias PageRank on, in order to improve topic specific search.

REFERENCES

• 1: Paul Alexandru Chirita , Wolfgang Nejdl , Raluca Paiu , Christian Kohlschütter, Using ODP metadata to personalize search, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, August 15-19, 2005, Salvador, Brazil [doi>10.1145/1076034.1076067]
• 2: Taher H. Haveliwala, Topic-sensitive PageRank, Proceedings of the 11th international conference on World Wide Web, May 07-11, 2002, Honolulu, Hawaii, USA [doi>10.1145/511446.511513]
• 3: M. Kendall. Rank Correlation Methods. Hafner, 1955.
• 4: L. Page, S. Brin, R. Motwani, and T. Winograd. The PageRank citation ranking: Bringing order to the web. Technical report, Stanford University, 1998.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Design, Experimentation

Keywords:
biased PageRank, open directory, personalized search