Discriminative training of clustering functions: Theory and experiments with entity identification

CoNLL 2005 - Proceedings of the Ninth Conference on Computational Natural Language Learning

Volumn , Issue , 2005, Pages 64-71

  Li, Xin ^a   Roth, Dan ^a  

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

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING APPROACH; DISCRIMINATIVE TRAINING; DISTANCE METRICS; ENTITY IDENTIFICATION; LEARNING TASKS; NATURAL LANGUAGE PROCESSING; OPTIMIZATION PROCEDURES; PERFORMANCE IMPROVEMENTS;

CLUSTERING ALGORITHMS; COMPUTATIONAL LINGUISTICS; EXPERIMENTS; OPTIMIZATION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84862294955     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. F. R. Bach and M. I. Jordan. 2003. Learning spectral clustering. In NIPS-03.
2. A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall. 2003. Learning distance functions using equivalence relations. In ICML-03, pages 11-18.
3. M. Bilenko, R. Mooney, W. Cohen, P. Ravikumar, and S. Fienberg. 2003. Adaptive name matching in information integration. IEEE Intelligent Systems, pages 16-23.
4. M Bilenko, S. Basu, and R. J. Mooney. 2004. Integrating constraints and metric learning in semi-supervised clustering. In ICML-04, pages 81-88.
5. P. Brown, P. deSouza R. Mercer, V. Pietra, and J. Lai. 1992. Class-based n-gram models of natural language. Computational Linguistics, 18(4):467-479.
6. C. Cardie and K. Wagstaff. 1999. Noun phrase coreference as clustering. In EMNLP-99, pages 82-89.
7. S. C. Chu, J. F. Roddick, and J. S. Pan. 2001. A comparative study and extensions to k-medoids algorithms. In ICOTA-01.
8. W. Cohen and J. Richman. 2002. Learning to match and cluster large high-dimensional data sets for data integration. In KDD-02, pages 475-480.
9. W. Cohen, P. Ravikumar, and S. Fienberg. 2003. A comparison of string metrics for name-matching tasks. In IIWeb Workshop 2003, pages 73-78.
10. I. Dagan, L. Lee, and F. Pereira. 1999. Similarity-based models of word cooccurrence probabilities. Machine Learning, 34(1-3):43-69.
11. Y. Freund and R. Schapire. 1998. Large margin classification using the Perceptron algorithm. In COLT-98.
12. M. Geffet and I. Dagan. 2004. Automatic feature vector quality and distributional similarity. In COLING-04.
13. K. George. 2003. Cluto: A clustering toolkit. Technical report, Dept of Computer Science, University of Minnesota.
14. J. Hartigan and M. Wong. 1979. A k-means clustering algorithm. Applied Statistics, 28(1):100-108.
15. S. Kamvar, D. Klein, and C. Manning. 2002. Interpreting and extending classical agglomerative clustering algorithms using a model-based approach. In ICML-02, pages 283-290.
16. L. Lee. 1997. Similarity-Based Approaches to Natural Language Processing. Ph.D. thesis, Harvard University, Cambridge, MA.
17. X. Li, P. Morie, and D. Roth. 2004. Identification and tracing of ambiguous names: Discriminative and generative approaches. In AAAI-04, pages 419-424.
18. G. Mann and D. Yarowsky. 2003. Unsupervised personal name disambiguation. In CoNLL-03, pages 33-40.
19. A. McCallum and B. Wellner. 2003. Toward conditional models of identity uncertainty with application to proper noun coreference. In IJCAI Workshop on Information Integration on the Web.
20. D. Mochihashi, G. Kikui, and K. Kita. 2004. Learning nonstructural distance metric by minimum cluster distortions. In COLING-04.
21. P. Pantel and D. Lin. 2002. Discovering word senses from text. In KDD-02, pages 613-619.
22. D. Roth. 1998. Learning to resolve natural language ambiguities: A unified approach. In AAAI-98, pages 806-813.
23. M. Schultz and T. Joachims. 2004. Learning a distance metric from relative comparisons. In NIPS-04.
24. E. Voorhees. 2002. Overview of the TREC-2002 question answering track. In TREC-02, pages 115-123.
25. J. Weeds, D. Weir, and D. McCarthy. 2004. Characterising measures of lexical distributional similarity. In COLING-04.
26. E. P. Xing, A. Y. Ng, M. I. Jordan, and S. Russell. 2002. Distance metric learning, with application to clustering with side-information. In NIPS-02.