Colin Cherry and Dekang Lin. 2003. A Probability Model to Improve Word Alignment. In Proceedings of ACL 2003, pp. 88--95. Sapporo, Japan. [PDF][PS]

Dekang Lin and Colin Cherry. 2003. Word Alignment with Cohesion Constraint. In Proceedings of HLT/NAACL 2003. Companion Volume, pp. 49-51, Edmonton, Canada. [PDF][PS]

Dekang Lin, Shaojun Zhao, Lijuan Qin and Ming Zhou. 2003. Identifying Synonyms among Distributionally Similar Words. In Proceedings of IJCAI-03, pp.1492-1493. [PDF][PS]

Patrick Pantel and Dekang Lin. 2002. Discovering Word Senses from Text. In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2002. pp. 613-619. Edmonton, Canada. [PDF][PS]

Dekang Lin and Patrick Pantel. 2002. Concept Discovery from Text. In Proceedings of Conference on Computational Linguistics 2002. pp. 577-583. Taipei, Taiwan. [PDF][PS]

Patrick Pantel and Dekang Lin. 2002. Document Clustering with Committees. In Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval 2002. pp. 199-206. Tampere, Finland. [PDF][PS]

Bonnie J. Dorr, Gina-Anne Levow, and Dekang Lin, Construction of a Chinese-English Verb Lexicon for Embedded Machine Translation in Cross-Language Information Retrieval, Machine Translation, Special Issue on Embedded MT. [PDF][PS]

Dekang Lin and Patrick Pantel. 2001. Discovery of Inference Rules for Question Answering. Natural Language Engineering 7(4):343-360. [PDF][PS]

D. Lin and P. Pantel. 2001. Induction of Semantic Classes from Natural Language Text. In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2001. pp. 317-322. [PDF][PS]

D. Lin and P. Pantel. 2001. DIRT - Discovery of Inference Rules from Text. In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2001. pp. 323-328. [PDF][PS]

P. Pantel and D. Lin. 2001. A Statistical Corpus-Based Term Extractor. In: Stroulia, E. and Matwin, S. (Eds.) AI 2001, Lecture Notes in Artificial Intelligence. pp. 36-46. Springer-Verlag. [PDF][PS]

D. Lin. 2001. LaTaT: Language and Text Analysis Tools. In Proceedings of Human Language Technology Conference 2001. pp.222--227. 2001. [PDF]

P. Pantel and D. Lin. 2000. An Unsupervised Approach to Prepositional Phrase Attachment using Contextually Similar Words. In Proceedings of Association for Computational Linguistics 2000. pp. 101-108. Hong Kong. [PDF][PS]

P. Pantel and D. Lin, 2000. Word-for-Word Glossing with Contextually Similar Words, In Proceedings of ANLP-NAACL 2000, pp.78-85, Seattle, Washington, May 2000. [PDF][PS]

B.J. Dorr, G. Levow, D. Lin, "Building a Chinese-English Mapping Between Verb Concepts for Multilingual Applications," Proceedings of the Fourth Conference of the Association for Machine Translation in the Americas (AMTA), Cuernavaca, Mexico, 2000, pp. 1--12. [PDF]

D. Lin, 1999. Automatic Identification of Non-compositional Phrases, In Proceedings of ACL-99, pp.317-324. University of Maryland, Colledge Park, Maryland, June, 1999. [PDF][PS]

D. Lin, 1998. Automatic Retrieval and Clustering of Similar Words. COLING-ACL98, Montreal, Canada, August, 1998. [PDF][PS]

D. Lin, 1998. An Information-Theoretic Definition of Similarity. Proceedings of International Conference on Machine Learning, Madison, Wisconsin, July, 1998. [PDF][PS]

D. Lin, 1998. Extracting Collocations from Text Corpora. First Workshop on Computational Terminology, Montreal, Canada, August, 1998.

D. Lin, 1998. Dependency-based Evaluation of MINIPAR. In Workshop on the Evaluation of Parsing Systems,
Granada, Spain, May, 1998.

D. Lin, 1997. Using Syntactic Dependency as Local Context to Resolve Word Sense Ambiguity In Proceedings of ACL-97, Madrid, Spain. July, 1997.

D. Lin, 1996. On Structural Complexity, in Proceedings of COLING-96, Copenhagen, Denmark. [PDF]

D. Lin. 1995a University of Manitoba: Description of the PIE System as Used for MUC-6 . In Proceedings of the Sixth Conference on Message Understanding (MUC-6), Columbia, Maryland.

D. Lin. 1995a Program Recognition by Observation. In IJCAI 95 Workshop on Plan Recognition

D. Lin. 1995b A Dependency-based Method for Evaluating Broad-Coverage Parsers. To appear in Proceedings of IJCAI-95

D. Lin, A Dependency-based Method for Evaluating Broad-Coverage Parsers. Natural Language Engineering. 1998.

B.J. Dorr and D. Lin, J. Lee, and S. Suh. 1995. Efficient Parsing for Korean and English: A Parameterized Message Passing Approach, Computational Linguistics, pp. 255-263. vol. 21, no. 2. June, 1995.

D. Lin, 1994. PRINCIPAR---An Efficient, broad-coverage, principle-based parser. In Proceedings of COLING-94. pp.42--488, Kyoto, Japan.

D. Lin, 1993a. Principle-based Parsing without Overgeneration. In Proceedings of ACL-93, pp.112--120, Columbus, Ohio.

D. Lin, 1993b. University of Manitoba: Description of the NUBA System as Used for MUC-5 . In Proceedings of the Fifth Conference on Message Understanding MUC-5, pp.263--275, ARPA, Baltimore, Maryland.

D. Lin and R. Goebel, 1993. Contex-Free Grammar Parsing by Message Passing. In Proceedings of PACLING--93, pp.203--211, Vancouver, BC.

D. Lin, 1992. A probabilistic network of predicates. In Uncertainty in AI: Proceedings of the Eighth Conference . pp.174--181, Mortgan Kaufmann Publishers.

D. Lin, 1992. Obvious Abduction, Ph.D. dissertation, University of Alberta.

D. Lin and R. Goebel, 1991. A message passing algorithm for plan recognition. In Proceedings of IJCAI-91, pp.280285, Sydney, Australia, 1991. [PDF]

D. Lin and R. Goebel, 1990. A minimal connection model of abductive diagnostic reasoning. In Proceedings of 1990 IEEE Conference on Artificial Intelligence Applications, pp. 16-22. Santa Barbara, California.