Selective hypertext induced topic search

ABSTRACT

We address the problem of answering broad-topic queries on the World Wide Web. We present a link based analysis algorithm SelHITS, which is an improvement over Kleinberg's HITS [2] algorithm. We introduce the concept of virtual links to exploit the latent information in the hyperlinked environment. We propose a novel approach to calculate hub and authority values. We also present a selective expansion method which avoids topic drift and provides results consistent with only one interpretation of the query, even if the query is ambiguous. Initial experimental evaluation and user feedback show that our algorithm indeed distills the most important and relevant pages for broad-topic queries. We also infer that there exists a uniform notion of quality of search results within users.

REFERENCES

• 1: More details about experiments on SelHITS algorithm. http://www4.ncsu.edu/~acawekar/'SelHITSResults/.
• 2: Jon M. Kleinberg, Authoritative sources in a hyperlinked environment, Journal of the ACM (JACM), v.46 n.5, p.604-632, Sept. 1999 [doi>10.1145/324133.324140]
• 3: Amy N. Langville , Carl D. Meyer, A Survey of Eigenvector Methods for Web Information Retrieval, SIAM Review, v.47 n.1, p.135-161, 2005 [doi>10.1137/S0036144503424786]

INDEX TERMS

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

General Terms:
Algorithms

Keywords:
link analysis, searching, topic distillation