Incremental diversification for very large sets: A streaming-based approach

SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2011, Pages 585-594

  Minack, Enrico ^a   Siberski, Wolf ^a   Nejdl, Wolfgang ^a  

^a L3S RESEARCH CENTER   (Germany)

Author keywords

Approximation; Diversification; Large sets; Streams

Indexed keywords

INFORMATION SERVICES;

APPROXIMATION; CONSTANT MEMORY; CONTINUOUS DATA; CONTINUOUS QUERIES; DIVERSIFICATION; LARGE SETS; LINEAR COMPUTATIONS; STREAMS;

OPTIMIZATION;

EID: 80052136714     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2009916.2009996     Document Type: Conference Paper

References (29)

1. R. Agrawal, S. Gollapudi, A. Halverson, and S. Ieong. Diversifying search results. In WSDM, 2009.
2. S. Babu and J. Widom. Continuous queries over data streams. SIGMOD Record, 30(3):109-120, 2001. (Pubitemid 33610406)
3. D. F. Barbieri, D. Braga, S. Ceri, E. D. Valle, and M. Grossniklaus. C-sparql: Sparql for continuous querying. In WWW, 2009.
4. J. G. Carbonell and J. Goldstein. The use of MMR, diversity-based reranking for reordering documents and producing summaries. In SIGIR, 1998.
5. H. Chen and D. R. Karger. Less is more: probabilistic models for retrieving fewer relevant documents. In SIGIR, 2006.
6. J. Chen, D. J. DeWitt, F. Tian, and Y. Wang. NiagaraCQ: a scalable continuous query system for internet databases. In ACM SIGMOD, 2000.
7. C. L. Clarke, M. Kolla, G. V. Cormack, O. Vechtomova, A. Ashkan, S. Büttcher, and I. MacKinnon. Novelty and diversity in information retrieval evaluation. In SIGIR, 2008.
8. M. Drosou and E. Pitoura. Comparing diversity heuristics. Technical Report TR-2009-05, Comp. Sci. Department, University of Ioannina, Greece, 2009.
9. M. Drosou and E. Pitoura. Diversity over continuous data. IEEE Data Eng. Bull., 32(4):49-56, 2009.
10. M. Drosou, K. Stefanidis, and E. Pitoura. Preference-aware publish/subscribe delivery with diversity. In DEBS, 2009.
11. F. Giunchiglia. Managing Diversity in Knowledge. In IEA/AIE 2006, LNAI 4031, page 1, 2006.
12. S. Gollapudi and A. Sharma. An axiomatic approach for result diversification. In WWW, 2009.
13. J. R. Haritsa. The KNDN problem: A quest for unity in diversity. IEEE Data Eng. Bull., 32(4):15-22, 2009.
14. V. Hristidis, O. Valdivia, M. Vlachos, and P. S. Yu. A system for keyword search on textual streams. In SDM, 2007.
15. U. Irmak, S. Mihaylov, T. Suel, S. Ganguly, and R. Izmailov. Efficient query subscription processing for prospective search engines. In USENIX, 2006.
16. D. E. Knuth. Sorting and Searching, volume 3 of The Art of Computer Programming. Addison Wesley, 1973.
17. D. G. McDonald and J. Dimmick. The conceptualization and measurement of diversity. Communication Research, 30(1):60-79, 2003.
18. E. Minack, G. Demartini, and W. Nejdl. Current approaches to search result diversification. In LivingWeb Workshop at ISWC, 2009.
19. G. Mishne and M. de Rijke. A study of blog search. In ECIR, 2006.
20. T.-W. Ryu, T. wan Ryu, and C. F. Eick. A unified similarity measure for attributes with set or bag of values. In RSDMGrC, 1998.
21. R. L. T. Santos, C. Macdonald, and I. Ounis. Exploiting query reformulations for web search result diversification. In WWW, 2010.
22. D. Skoutas, E. Minack, and W. Nejdl. Dealing with diversity in web search results. In WebSci10, 2010.
23. A. Slivkins, F. Radlinski, and S. Gollapudi. Learning optimally diverse rankings over large document collections. In ICML, 2010.
24. E. Vee, U. Srivastava, J. Shanmugasundaram, P. Bhat, and S. A. Yahia. Efficient computation of diverse query results. In ICDE, 2008.
25. J. Wang and J. Zhu. Portfolio theory of information retrieval. In SIGIR, 2009.
26. C. Yu, L. Lakshmanan, and S. Amer-Yahia. It takes variety to make a world: diversification in recommender systems. In EDBT, 2009.
27. C. Zhai, W. W. Cohen, and J. D. Lafferty. Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. In SIGIR, 2003.
28. C. Zhai and J. D. Lafferty. A risk minimization framework for information retrieval. Inf. Process. Manage., 42(1):31-55, 2006. (Pubitemid 41130281)
29. C.-N. Ziegler, S. M. McNee, J. A. Konstan, and G. Lausen. Improving recommendation lists through topic diversification. In WWW, 2005.