Exploiting query reformulations for web search result diversification

Proceedings of the 19th International Conference on World Wide Web, WWW '10

Volumn , Issue , 2010, Pages 881-890

  Santos, Rodrygo L T ^a   Macdonald, Craig ^a   Ounis, Iadh ^a  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

diversity; relevance; web search

Indexed keywords

DOCUMENT RANKING; INFORMATION NEED; PROBABILISTIC FRAMEWORK; QUERY REFORMULATION; WEB SEARCH ENGINES; WEB SEARCHES; WEB USERS;

INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS; SEARCH ENGINES;

WORLD WIDE WEB;

EID: 77954606687     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1772690.1772780     Document Type: Conference Paper

References (33)

1. R. Agrawal, S. Gollapudi, A. Halverson, and S. Ieong. Diversifying search results. In Proc. of WSDM, pages 5-14, 2009.
2. G. Amati, E. Ambrosi, M. Bianchi, C. Gaibisso, and G. Gambosi. FUB, IASI-CNR and University of Tor Vergata at TREC 2007 Blog track. In Proc. of TREC, 2007.
3. R. A. Baeza-Yates, C. A. Hurtado, and M. Mendoza. Query recommendation using query logs in search engines. In Proc. of EDBT Workshops, pages 588-596, 2004.
4. P. Boldi, F. Bonchi, C. Castillo, and S. Vigna. From "Dango" to "Japanese cakes": query reformulation models and patterns. In Proc. of WI-IAT, pages 183-190, 2009.
5. J. Carbonell and J. Goldstein. The use of MMR, diversity-based reranking for reordering documents and producing summaries. In Proc. of SIGIR, pages 335-336, 1998.
6. B. Carterette. An analysis of NP-completeness in novelty and diversity ranking. In Proc. of ICTIR, pages 200-211, 2009.
7. B. Carterette and P. Chandar. Probabilistic models of ranking novel documents for faceted topic retrieval. In Proc. of CIKM, pages 1287-1296, 2009.
8. H. Chen and D. R. Karger. Less is more: probabilistic models for retrieving fewer relevant documents. In Proc. of SIGIR, pages 429-436, 2006.
9. C. L. A. Clarke, N. Craswell, and I. Soboroff. Preliminary report on the TREC 2009 Web track. In Proc. of TREC, 2009.
10. C. L. A. Clarke, M. Kolla, G. V. Cormack, O. Vechtomova, A. Ashkan, S. Büttcher, and I. MacKinnon. Novelty and diversity in information retrieval evaluation. In Proc. of SIGIR, pages 659-666, 2008.
11. C. L. A. Clarke, M. Kolla, and O. Vechtomova. An effectiveness measure for ambiguous and underspecified queries. In Proc. of ICTIR, pages 188-199, 2009.
12. W. S. Cooper. The inadequacy of probability of usefulness as a ranking criterion for retrieval system output. Technical report, Univ. of California, 1971.
13. W. Goffman. On relevance as a measure. IP&M, 2(3):201-203, 1964.
14. S. Gollapudi and A. Sharma. An axiomatic approach for result diversification. In Proc. of WWW, pages 381-390, 2009.
15. B. He, C. Macdonald, I. Ounis, J. Peng, and R. L. T. Santos. University of Glasgow at TREC 2008: experiments in Blog, Enterprise, and Relevance Feedback tracks with Terrier. In Proc. of TREC, 2008.
16. M. A. Hearst. Search User Interfaces. Cambridge University Press, 2009.
17. D. Hiemstra. Using Language Models for Information Retrieval. PhD thesis, Univ. of Twente, 2001.
18. D. S. Hochbaum, editor. Approximation algorithms for NP-hard problems. PWS Publishing Co., 1997.
19. B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: a study of user queries on the Web. SIGIR Forum, 32(1):5-17, 1998.
20. K. Järvelin and J. Kekäläinen. Cumulated gain-based evaluation of IR techniques. ACM TOIS, 20(4):422-446, 2002.
21. I. Ounis, G. Amati, V. Plachouras, B. He, C. Macdonald, and C. Lioma. Terrier: a high performance and scalable information retrieval platform. In Proc. of SIGIR, OSIR Workshop, 2006.
22. J. Peng, C. Macdonald, B. He, V. Plachouras, and I. Ounis. Incorporating term dependency in the DFR framework. In Proc. of SIGIR, pages 843-844, 2007.
23. F. Radlinski and S. Dumais. Improving personalized web search using result diversification. In Proc. of SIGIR, pages 691-692, 2006.
24. S. E. Robertson. The probability ranking principle in IR. Journal of Documentation, 33(4):294-304, 1977.
25. S. E. Robertson, S. Walker, S. Jones, M. Hancock-Beaulieu, and M. Gatford. Okapi at TREC-3. In Proc. of TREC, 1994.
26. J. J. Rocchio. Relevance feedback in information retrieval. In The SMART Retrieval System, pages 313-323. 1971.
27. R. L. T. Santos, J. Peng, C. Macdonald, and I. Ounis. Explicit search result diversification through sub-queries. In Proc. of ECIR, 2010.
28. M. Shokouhi. Central-rank-based collection selection in uncooperative distributed information retrieval. In Proc. of ECIR, pages 160-172, 2007.
29. K. Spärck-Jones, S. E. Robertson, and M. Sanderson. Ambiguous requests: implications for retrieval tests, systems and theories. SIGIR Forum, 41(2):8-17, 2007.
30. J. Wang and J. Zhu. Portfolio theory of information retrieval. In Proc. of SIGIR, pages 115-122, 2009.
31. J. Yi and F. Maghoul. Query clustering using click-through graph. In Proc. of WWW, pages 1055-1056, 2009.
32. H.-J. Zeng, Q.-C. He, Z. Chen, W.-Y. Ma, and J. Ma. Learning to cluster Web search results. In Proc. of SIGIR, pages 210-217, 2004.
33. C. Zhai, W. W. Cohen, and J. Lafferty. Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. In Proc. of SIGIR, pages 10-17, 2003.