Context-Sensitive Convolution Tree Kernel for Pronoun Resolution

IJCNLP 2008 - 3rd International Joint Conference on Natural Language Processing, Proceedings of the Conference

Volumn 1, Issue , 2008, Pages 25-31

  Zhou, GuoDong ^a   Kong, Fang ^a   Zhu, Qiaoming ^a  

^a SOOCHOW UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EXPANSION; FORESTRY; NATURAL LANGUAGE PROCESSING SYSTEMS;

ANAPHORS; CONTEXT-FREE; CONTEXT-SENSITIVE; CRITICAL PROBLEMS; DYNAMIC EXPANSION; PARSE TREES; PRONOUN RESOLUTION; SUB TREES; TREE KERNELS; TWO WAYS;

CONVOLUTION;

EID: 77950894698     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Aone C and Bennett W.W. (1995). Evaluating automated and manual acquisition of anaphora resolution strategies. ACL'1995:122-129.
2. Bergsma S. and Lin D.K.(2006). Bootstrapping pathbased pronoun resolution. COLING-ACL'2006: 33- 40.
3. Charniak E. (2001). Immediate-head Parsing for Language Models. ACL'2001: 129-137. Toulouse, France.
4. Collins M. (1999) Head-driven statistical models for natural language parsing. Ph.D. Thesis. University of Pennsylvania.
5. Collins M. and Duffy N. (2001). Convolution Kernels for Natural Language. NIPS'2001: 625-632. Cambridge, MA.
6. Culotta A. and Sorensen J. (2004). Dependency tree kernels for relation extraction. ACL'2004. 423-429. 21-26 July 2004. Barcelona, Spain.
7. Haussler D. (1999). Convolution Kernels on Discrete Structures. Technical Report UCS-CRL-99-10, University of California, Santa Cruz.
8. Hobbs J. (1978). Resolving pronoun references. Lingua. 44:339-352.
9. Joachims T. (1998). Text Categorization with Support Vector Machine: learning with many relevant features. ECML-1998: 137-142. Chemnitz, Germany.
10. Lappin S. and Leass H. (1994). An algorithm for pronominal anaphora resolution. Computational Linguistics. 20(4):526-561.
11. Mitkov R. (1998). Robust pronoun resolution with limited knowledge. COLING-ACL'1998:869-875. Montreal, Canada.
12. Moschitti A. (2004). A study on convolution kernels for shallow semantic parsing. ACL'2004:335-342.
13. Pradhan S., Hacioglu K., Krugler V., Ward W., Martin J.H. and Jurafsky D. (2005). Support Vector Learning for Semantic Argument Classification. Machine Learning. 60(1):11-39.
14. Soon W. Ng H.T.and Lim D. (2001). A machine learning approach to creference resolution of noun phrases. Computational Linguistics. 27(4): 521-544.
15. Yang X.F., Zhou G.D., Su J. and Tan C.L., Coreference Resolution Using Competition Learning Approach, ACL'2003):176-183. Sapporo, Japan, 7-12 July 2003.
16. Yang X.F., Su J. and Tan C.L. (2006). Kernel-based pronoun resolution with structured syntactic knowledge. COLING-ACL'2006: 41-48.
17. Zelenko D., Aone C. and Richardella. (2003). Kernel methods for relation extraction. Journal of Machine Learning Research. 3(Feb):1083-1106.
18. Zhang M., Zhang J., Su J. and Zhou G.D. (2006). A Composite Kernel to Extract Relations between Entities with both Flat and Structured Features.
19. COLING-ACL-2006: 825-832. Sydney, Australia Zhou G.D., Su J. Zhang J. and Zhang M. (2005). Exploring various knowledge in relation extraction. ACL'2005. 427-434. 25-30 June, Ann Arbor, Michgan, USA.
20. Zhou G.D., Zhang M., Ji D.H. and Zhu Q.M. (2007). Tree Kernel-based Relation Extraction with Context- Sensitive Structured Parse Tree Information. EMNLP-CoNLL'2007.