An unsupervised learning algorithm for rank aggregation

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

Volumn 4701 LNAI, Issue , 2007, Pages 616-623

  Klementiev, Alexandre ^a   Roth, Dan ^a   Small, Kevin ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA FUSION; DATA MINING; INFORMATION RETRIEVAL; NATURAL LANGUAGE PROCESSING SYSTEMS; UNSUPERVISED LEARNING;

RANK AGGREGATION; RANKING MODELS;

LEARNING ALGORITHMS;

EID: 38049129511     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74958-5_60     Document Type: Conference Paper

References (18)

1. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press / Addison-Wesley (1999)
2. Cohen, W.W., Schapire, R.E., Singer, Y.: Learning to order things. Journal of Artificial Intelligence Research 10, 243-270 (1999)
3. Agarwal, S., Roth, D.: Learnability of bipartite ranking functions. In: Proc. of the Annual ACM Workshop on Computational Learning Theory (COLT), pp. 16-31 (2005)
4. Clémençon, S., Lugosi, G., Vayatis, N.: Ranking and scoring using empirical risk minimization. In: Proc. of the Annual ACM Workshop on Computational Learning Theory (COLT), pp. 1-15 (2005)
5. Rudin, C., Cortes, C., Mohri, M., Schapire, R.E.: Margin-based ranking and boosting meet in the middle. In: Proc. of the Annual ACM Workshop on Computational Learning Theory (COLT), pp. 63-78 (2005)
6. Collins, M., Koo, T.: Discriminative reranking for natural language parsing. In: Proc. of the International Conference on Machine Learning (ICML), pp. 175-182 (2000)
7. Li, H., Rudin, C., Grishman, R.: Re-ranking algorithms for name tagging. In: HLT/NAACL Workshop on Joint Inference (2006)
8. Klementiev, A., Roth, D.: Weakly supervised named entity transliteration and discovery from multilingual comparable corpora. In: Proc. of the Annual Meeting of the Association for Computational Linguistics (ACL), pp. 817-824 (2006)
9. Lillis, D., Toolan, F., Collier, R., Dunnion, J.: Probfuse: A probabilistic approach to data fusion. In: Proc. of the International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 139-146 (2006)
10. Vogt, C.C., Cottrell, G.W.: Fusion via a linear combination of scores. Information Retrieval 1(3), 151-173 (1999)
11. Cesa-Bianchi, N., Freund, Y., Helmbold, D.P., Haussler, D., Schapire, R.E., Warmuth, M.K.: How to use expert advice. Journal of the Association for Computing Machinery 44(3), 427-485 (1997)
12. Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences 55(1), 119-139 (1997)
13. Conitzer, V.: Computational Aspects of Preference Aggregation. PhD thesis, Carnegie Mellon University (2006)
14. Arrow, K.: Social Choice and Individual Values, 2nd edn. Cowles Foundation, New Haven (1963)
15. Shaw, J.A., Fox, E.A.: Combination of multiple searches. In: Text REtrieval Conference (TREC), pp. 243-252 (1994)
16. Kendall, M., Gibbons, J.D.: Rank Correlation Methods, 5th edn. Edward Arnold, London (1990)
17. Kivinen, J., Warmuth, M.K.: Additive versus exponentiated gradient updates for linear prediction. In: Proc, of the Annual ACM Symposium on Theory of Computing, pp. 209-218 (1995)
18. Voorhees, E.M., Buckland, L.P. (eds.): The Fourteenth Text REtrieval Conference Proceedings (TREC) (2005)