Applying machine learning to Chinese temporal relation resolution

Proceedings of the Annual Meeting of the Association for Computational Linguistics

Volumn , Issue , 2004, Pages 582-588

  Li, Wenjie ^a   Wong, Kam Fai ^b   Cao, Guihong ^a   Yuan, Chunfa ^c  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^c TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS;

COMPUTATIONAL MODELLING; CONNECTIVE STRUCTURES; DISCOURSE STRUCTURE; LINGUISTIC FEATURES; MACHINE-LEARNING; MODEL-BASED OPC; ON-MACHINES; TEMPORAL INFORMATION; TEMPORAL RELATION; TEMPORAL STRUCTURES;

MACHINE LEARNING;

EID: 85120178147     PISSN: 0736587X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. Allen J., 1981. An Interval-based Represent Action of Temporal Knowledge. In Proceedings of 7th International Joint Conference on Artificial Intelligence, pages 221-226. Los Altos, CA.
2. Blum, A. and Mitchell T., 1998. Combining Labeled and Unlabeled Data with Co-Training. In Proceedings of the Eleventh Annual Conference on Computational Learning Theory, Madison, Wisconsin, pages 92-100
3. Bruce B., 1972. A Model for Temporal References and its Application in Question-Answering Program. Artificial Intelligence, 3(1):1-25.
4. Collins M. and Singer Y, 1999. Unsupervised Models for Named Entity Classification. In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, pages 189-196. University of Maryland.
5. Dorr B. and Gaasterland T., 2002. Constraints on the Generation of Tense, Aspect, and Connecting Words from Temporal Expressions. (submitted to JAIR)
6. Hitzeman J., Moens M. and Grover C., 1995. Algorithms for Analyzing the Temporal Structure of Discourse. In Proceedings of the 7th European Meeting of the Association for Computational Linguistics, pages 253-260. Dublin, Ireland.
7. Lascarides A., Asher N. and Oberlander J., 1992. Inferring Discourse Relations in Context. In Proceedings of the 30th Meeting of the Association for Computational Linguistics, pages 1-8, Newark, Del.
8. Li W.J. and Wong K.F., 2002. A Word-based Approach for Modeling and Discovering Temporal Relations Embedded in Chinese Sentences, ACM Transaction on Asian Language Processing, 1(3):173-206.
9. Ma J. and Knight B., 1994. A General Temporal Theory. The Computer Journal, 37(2):114- 123.
10. Màntaras L., 1991. A Distance-based Attribute Selection Measure for Decision Tree Induction. Machine Learning, 6(1): 81–92.
11. Màrquez L., Padró L. and Rodríguez H., 2000. A Machine Learning Approach to POS Tagging. Machine Learning, 39(1):59-91. Kluwer Academic Publishers.
12. Partee, B., 1984. Nominal and Temporal Anaphora. Linguistics and Philosophy, 7(3):287-324.
13. Quinlan J., 1993. C4.5 Programs for Machine Learning. Morgan Kauman Press.
14. Reichenbach H., 1947. Elements of Symbolic Logic. Berkeley CA, University of California Press.
15. Siegel E. and McKeown K., 2000. Learning Methods to Combine Linguistic Indicators: Improving Aspectual Classification and Revealing Linguistic Insights. Computational Linguistics, 26(4): 595-627.
16. Wiebe, J.M., O'Hara, T.P., Ohrstrom-Sandgren, T. and McKeever, K.J, 1998. An Empirical Approach to Temporal Reference Resolution. Journal of Artificial Intelligence Research, 9:247-293.
17. Wong F., Li W., Yuan C., etc., 2002. Temporal Representation and Classification in Chinese. International Journal of Computer Processing of Oriental Languages, 15(2):211-230.
18. Yarowsky D., 1994. Decision Lists for Lexical Ambiguity Resolution: Application to the Accent Restoration in Spanish and French. In Proceeding of the 32rd Annual Meeting of ACL, San Francisco, CA.
19. Zhou X., Dillon T., 1991. A Statistical-heuristic Feature Selection Criterion for Decision Tree Induction. IEEE Transaction on Pattern Analysis and Machine Intelligence, 13(8): 834-841.