Explicit search result diversification through sub-queries

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5993 LNCS, Issue , 2010, Pages 87-99

  Santos, Rodrygo L T ^a   Peng, Jie ^a   MacDonald, Craig ^a   Ounis, Iadh ^a  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

SEARCH ENGINES;

DOCUMENT RANKING; RETRIEVAL SYSTEMS; STATE OF THE ART; SUB-QUERIES; TREC COLLECTION;

INFORMATION RETRIEVAL;

EID: 77952313250     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12275-0_11     Document Type: Conference Paper

References (21)

1. Sp̈arck-Jones, K., Robertson, S.E., Sanderson, M.: Ambiguous requests: implications for retrieval tests, systems and theories. SIGIR Forum 41(2), 8-17 (2007)
2. Robertson, S.E.: The probability ranking principle in IR. Journal of Documentation 33(4), 294-304 (1977)
3. Clarke, C.L., Kolla, M., Cormack, G.V., Vechtomova, O., Ashkan, A., B̈uttcher, S., MacKinnon, I.: Novelty and diversity in information retrieval evaluation. In: SIGIR, pp. 659-666 (2008)
4. Agrawal, R., Gollapudi, S., Halverson, A., Ieong, S.: Diversifying search results. In: WSDM, pp. 5-14 (2009)
5. Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: SIGIR, pp. 335-336 (1998)
6. Hochbaum, D.S. (ed.): Approximation algorithms for NP-hard problems. PWS Publishing Co. (1997)
7. Zhai, C., Cohen, W.W., Lafferty, J.: Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. In: SIGIR, pp. 10-17 (2003)
8. Wang, J., Zhu, J.: Portfolio theory of information retrieval. In: SIGIR, pp. 115-122 (2009)
9. Radlinski, F., Dumais, S.: Improving personalized web search using result diversification. In: SIGIR, pp. 691-692 (2006)
10. Mihalcea, R.: Using Wikipedia for automatic word sense disambiguation. In: HLTNAACL, pp. 196-203 (2007)
11. Zeng, H.J., He, Q.C., Chen, Z., Ma, W.Y., Ma, J.: Learning to cluster web search results. In: SIGIR, pp. 210-217 (2004)
12. MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Berkeley SMSP, pp. 281-297 (1967)
13. Amati, G.: Probability models for information retrieval based on Divergence From Randomness. PhD thesis, University of Glasgow (2003)
14. Callan, J.: Distributed information retrieval. In: Croft, W.B. (ed.) Advances in Information Retrieval, pp. 127-150. Kluwer Academic Publishers, Dordrecht (2000)
15. Si, L., Callan, J.: Relevant document distribution estimation method for resource selection. In: SIGIR, pp. 298-305 (2003)
16. Shokouhi, M.: Central-rank-based collection selection in uncooperative distributed information retrieval. In: ECIR, pp. 160-172 (2007)
17. Ounis, I., Amati, G., Plachouras, V., He, B., Macdonald, C., Lioma, C.: Terrier: a high performance and scalable information retrieval platform. In: SIGIR/OSIR (2006)
18. Hersh, W., Over, P.: TREC-8 Interactive track report. In: TREC (2000)
19. Robertson, S.E., Walker, S., Hancock-Beaulieu, M., Gull, A., Lau, M.: Okapi at TREC. In: TREC (1992)
20. Amati, G., Ambrosi, E., Bianchi, M., Gaibisso, C., Gambosi, G.: FUB, IASI-CNR and University of Tor Vergata at TREC 2007 Blog track. In: TREC (2007)
21. J̈arvelin, K., Kek̈al̈ainen, J.: Cumulated gain-based evaluation of IR techniques. ACM TOIS 20(4), 422-446 (2002)