The factors affecting the performance of data fusion algorithms

Proceedings - 2009 International Conference on Information Management and Engineering, ICIME 2009

Volumn , Issue , 2009, Pages 465-470

  Nassar, Mohammad Othman ^a   Kanaan, Ghassan ^a  

^a Arab Academy for Banking and Financial Sciences Jordan   (Jordan)

Author keywords

Data fusion algorithms; Information retrieval; Information systems; Metasearch engines; Performance

Indexed keywords

DATA FUSION ALGORITHM; DATA-FUSION ALGORITHMS; DOCUMENT RETRIEVAL; METASEARCH; METASEARCH ENGINES; PERFORMANCE; RETRIEVAL PERFORMANCE; SINGLE SOURCE; STANDARD INFORMATION;

ALGORITHMS; DATA FUSION; ENGINES; INFORMATION FUSION; INFORMATION MANAGEMENT; INFORMATION SERVICES; INFORMATION SYSTEMS; SEARCH ENGINES; WORLD WIDE WEB;

INFORMATION RETRIEVAL;

EID: 70349512191     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIME.2009.44     Document Type: Conference Paper

References (22)

1. Milad Shokouhi, "Segmentation of search engine results for effective data-fusion", ECIR 2007, LNCS 4425, Springer Berlin / Heidelberg,2007, pp. 185-197.
2. Edward Fox, and Joseph Shaw, "Combination of multiple searches", editor, D. K. Harman, In Proc. Second Text REtrieval Conf., National Institute of standards and technology (NIST) Special Publication 500-215, Gaithersburg, Maryland, 1993, pp. 243-252.
3. Alexandre Klementiev, Dan Roth, and Kevin Small, "An unsupervised learning algorithm for rank aggregation", in Proc. European Conf. on Machine Learning, LNAI 4701, Springer Berlin / Heidelberg, 2007, pp. 616-623.
4. Javed Aslam, and Mark Montague, "Models for Metasearch", In Proc. ACM SIGIR 2001 Conf., ACM press, New Orleans, Louisiana, 2001, pp. 276-284.
5. Mark Montague, and Javed Aslam, "Condorcet fusion for improved retrieval", In Proc. Eleventh International Conf. on Information and Knowledge Management, ACM press, Virginia, USA, 2002, pp. 538-548.
6. Christopher Vogt, "How much more is better? Characterizing the effects of adding more IR systems to a combination", In Content-Based Multimedia Information Access, Paris, France, 2000, pp. 457-475.
7. Christopher Vogt, and Garrison Cottrell, "Fusion via a linear combination of scores", Information Retrieval, 1(3), Oct. 1999, pp. 151-173.
8. Shengli Wu, and Sally McClean, "Performance prediction of data fusion for information retrieval", Information Processing and Management, Vol. 42, Issue 4, Elsevier, 2006, pp. 899-915.
9. Joon Ho Lee, "Analyses of multiple evidence combination", In Proc. of the 20th ACM SIGIR conf., editors, Nicholas J. Belkin, A. Desai Narasimhalu, and Peter Willett, ACM press, Philadelphia, USA, 1997, pp 267-276.
10. David Lillis, Fergus Toolan, Rem Collier, and John Dunnion, "ProbFuse: a probabilistic approach to data fusion", in Proc. 29th ACM SIGIR conf., ACM press, Seattle, Washington, USA, 2006, pp. 139-146.
11. Christopher Vogt, "Adaptive Combination of Evidence for Information Retrieval", PhD thesis, University of California, San Diego, 1999.
12. Steven Beitzel, Eric Jensen, Abdur Chowdhury, David Grossman, Ophir Frieder, and Nazli Goharian, "On fusion of effective retrieval strategies in the same information retrieval system", Journal of the American Society for Information Science and Technology, 55(10), 2004, pp.859-868.
13. Christopher Vogt, and Garrison Cottrell, "Predicting the performance of linearly combined IR systems", editors, W. Bruce Croft, Keith van Rijsbergen, and Ross Wilkinson, SIGIR 98: Proceedings of the Twenty First Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval, Melbourne, ACM Press,1998, pp. 190-196.
14. Ian Soboroff , Chrles Nicholas, and Patrick Cahan, "Ranking retrieval systems without relevance judgments", the 24tli Annual ACM Conference on Research and Development in Information Retrieval (SIGIR '01). New Orleans. LA, ACM press, 2001, pp. 66 - 73.
15. Kwong Bor Ng, and Paul Kantor, "Predicting the effectiveness of naive data fusion on the basis of system characteristics", Journal of the American Society for Information Science, 50(13), 2000, pp. 1177-1189.
16. M. Elena Renda, and Umberto Straccia, "Web metasearch: rank vs. score based rank aggregation methods", SAC '03: Proc. of the 2003 ACM symposium on Applied computing, Melbourne, Florida, ACM Press, 2003, pp. 841 - 846.
17. N. J. Belkin, P. Kantor, E.A. Fox, and J. A. Shaw, "Combining evidence of multiple query representation for information retrieval", Information Processing & Management, 31(3), 1995, pp. 431-448.
18. Shengli Wu, Fabio Crestani, "Data fusion with estimated weights", CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management, ACM Press, November 2002, pp. 648-651.
19. Mark Montague and Javed Aslam, "Relevance score normalization for Metasearch", In CIKM '01: Proceedings of the tenth international conference on Information and knowledge management, New York, NY, USA, ACM Press, 2001, pp. 427-433.
20. D. Frank Hsu1, Isak Taksa, "Comparing rank and score combination methods for data fusion in information retrieval", Information Retrieval, Volume 8, Number 3, Springer Berlin / Heidelberg, 2005, pp. 449-480.
21. Shengli Wu, Fabio Crestani, and Yaxin Bi, "Evaluating Score Normalization Methods in Data Fusion", editors, H.T. Ng et al, AIRS 2006, LNCS 4182, Springer Berlin / Heidelberg, 2006, pp. 642-648.
22. Shengli Wu, "Applying statistical principles to data fusion in information retrieval", Expert Systems with Applications: An International Journal, Volume 36 , Issue 2, March 2009, Pergamon Press, pp. 2997-3006.