Mining anchor text for query refinement

ABSTRACT

When searching large hypertext document collections, it is often possible that there are too many results available for ambiguous queries. Query refinement is an interactive process of query modification that can be used to narrow down the scope of search results. We propose a new method for automatically generating refinements or related terms to queries by mining anchor text for a large hypertext document collection. We show that the usage of anchor text as a basis for query refinement produces high quality refinement suggestions that are significantly better in terms of perceived usefulness compared to refinements that are derived using the document content. Furthermore, our study suggests that anchor text refinements can also be used to augment traditional query refinement algorithms based on query logs, since they typically differ in coverage and produce different refinements. Our results are based on experiments on an anchor text collection of a large corporate intranet.

REFERENCES

• 1: Peter Anick, Using terminological feedback for web search refinement: a log-based study, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, July 28-August 01, 2003, Toronto, Canada [doi>10.1145/860435.860453]
• 2: Peter G. Anick , Suresh Tipirneni, The paraphrase search assistant: terminological feedback for iterative information seeking, Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, p.153-159, August 15-19, 1999, Berkeley, California, United States [doi>10.1145/312624.312670]
• 3: Sergey Brin , Lawrence Page, The anatomy of a large-scale hypertextual Web search engine, Computer Networks and ISDN Systems, v.30 n.1-7, p.107-117, April 1, 1998
• 4: Andrei Broder, A taxonomy of web search, ACM SIGIR Forum, v.36 n.2, Fall 2002 [doi>10.1145/792550.792552]
• 5: E. W. Brown and H. A. Chong. The GURU system in TREC-6. In Text REtrieval Conference, pages 535--540, 1997.
• 6: Chris Buckley , Gerard Salton , James Allan, The effect of adding relevance information in a relevance feedback environment, Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, p.292-300, July 03-06, 1994, Dublin, Ireland
• 7: C. Buckley, G. Salton, J. Allan, and A. Singhal. Automatic query expansion using SMART: TREC 3. In Text REtrieval Conference, pages 69--80, 1994.
• 8: David Carmel , Eitan Farchi , Yael Petruschka , Aya Soffer, Automatic query wefinement using lexical affinities with maximal information gain, Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval, August 11-15, 2002, Tampere, Finland [doi>10.1145/564376.564427]
• 9: Soumen Chakrabarti , Byron Dom , Prabhakar Raghavan , Sridhar Rajagopalan , David Gibson , Jon Kleinberg, Automatic resource compilation by analyzing hyperlink structure and associated text, Proceedings of the seventh international conference on World Wide Web 7, p.65-74, April 1998, Brisbane, Australia
• 10: James W. Cooper , Roy J. Byrd, OBIWAN - A Visual Interface for Prompted Query Refinement, Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 2, p.277, January 06-09, 1998 [doi>10.1109/HICSS.1998.651710]
• 11: Nick Craswell , David Hawking , Stephen Robertson, Effective site finding using link anchor information, Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, p.250-257, September 2001, New Orleans, Louisiana, United States [doi>10.1145/383952.383999]
• 12: Cynthia Dwork , Ravi Kumar , Moni Naor , D. Sivakumar, Rank aggregation methods for the Web, Proceedings of the 10th international conference on World Wide Web, p.613-622, May 01-05, 2001, Hong Kong, Hong Kong [doi>10.1145/371920.372165]
• 13: Nadav Eiron , Kevin S. McCurley, Analysis of anchor text for web search, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, July 28-August 01, 2003, Toronto, Canada [doi>10.1145/860435.860550]
• 14: Ronald Fagin , Ravi Kumar , D. Sivakumar, Efficient similarity search and classification via rank aggregation, Proceedings of the 2003 ACM SIGMOD international conference on Management of data, June 09-12, 2003, San Diego, California [doi>10.1145/872757.872795]
• 15: Larry Fitzpatrick , Mei Dent, Automatic feedback using past queries: social searching?, Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval, p.306-313, July 27-31, 1997, Philadelphia, Pennsylvania, United States
• 16: William B. Frakes , Ricardo Baeza-Yates, Information retrieval: data structures and algorithms, Prentice-Hall, Inc., Upper Saddle River, NJ, 1992
• 17: Mei Kobayashi , Koichi Takeda, Information retrieval on the web, ACM Computing Surveys (CSUR), v.32 n.2, p.144-173, June 2000 [doi>10.1145/358923.358934]
• 18: Dawn Lawrie , W. Bruce Croft , Arnold Rosenberg, Finding topic words for hierarchical summarization, Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, p.349-357, September 2001, New Orleans, Louisiana, United States [doi>10.1145/383952.384022]
• 19: Wen-Hsiang Lu , Lee-Feng Chien , Hsi-Jian Lee, Translation of web queries using anchor text mining, ACM Transactions on Asian Language Information Processing (TALIP), v.1 n.2, p.159-172, June 2002 [doi>10.1145/568954.568958]
• 20: O. A. McBryan. GENVL and WWWW: Tools for taming the web. In World Wide Web Conference (WWW'94), Geneva, Switzerland, 1994.
• 21: L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.
• 22: Yonggang Qiu , Hans-Peter Frei, Concept based query expansion, Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval, p.160-169, June 27-July 01, 1993, Pittsburgh, Pennsylvania, United States [doi>10.1145/160688.160713]
• 23: Craig Silverstein , Hannes Marais , Monika Henzinger , Michael Moricz, Analysis of a very large web search engine query log, ACM SIGIR Forum, v.33 n.1, p.6-12, Fall 1999 [doi>10.1145/331403.331405]
• 24: Bienvenido Vélez , Ron Weiss , Mark A. Sheldon , David K. Gifford, Fast and effective query refinement, Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval, p.6-15, July 27-31, 1997, Philadelphia, Pennsylvania, United States
• 25: Jinxi Xu , W. Bruce Croft, Query expansion using local and global document analysis, Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval, p.4-11, August 18-22, 1996, Zurich, Switzerland [doi>10.1145/243199.243202]
• 26: J. Zien, J. Meyer, J. Tomlin, and J. Liu. Web query characteristics and their implications on search engines. IBM Research Report, RJ 10199, November 2000.

INDEX TERMS

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

Keywords:
anchor text, query refinement, rank, web search