Applying explanation - based learning to control and speeding - Up natural language generation

Proceedings of the Annual Meeting of the Association for Computational Linguistics

Volumn 1997-July, Issue , 1997, Pages 214-221

  Neumann, Giinter ^a  

^a GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; NATURAL LANGUAGE PROCESSING SYSTEMS;

AUTOMATIC EXTRACTION; DECISION-MAKING PROCESS; EXPLANATION BASED LEARNING; NATURAL LANGUAGE GENERATION;

DECISION MAKING;

EID: 84894761473     PISSN: 0736587X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Copestake, A., D. Flickinger, R. Malouf, S. Riehemann, and I. Sag. 1996. Translation using minimal recursion semantics. In Proceedings, 6th International Conference on Theoretical and Methodological Issues in Machine Translation.
2. Dale, R., W. Finkler, R. Kittredge, N. Lenke, G. Neumann, C. Peters, and M. Stede. 1994. Report from working group 2: Lexicalization and architecture. In W. Hoeppner, H. Horacek, and J. Moore, editors, Principles of Natural Language Generation, Dagstuhl-Seminar-Report; 93. Schlofl Dagstuhl, Saarland, Germany, Europe, pages 30-39.
3. Kay, M. 1996. Chart generation. In 3~th Annual Meeting of the Association for Computational Linguistics, Santa Cruz, Ca.
4. Krieger, Hans-Ulrich and Ulrich Sch~fer. 1994.
5. 7"Dt:-a type description language for constraint-based grammars. In Proceedings of the 15th International Conference on Computational Linguistics, COLING-9~, pages 893-899.
6. Minton, S., J. G. Carbonell, C. A. Knoblock, D. R.Kuokka, O. Etzioni, and Y.Gi. 1989. Explanation-based learning: A problem solving perspective. Artificial Intelligence, 40:63-115.
7. Mitchell, T., R. Keller, and S. Kedar-Cabelli. 1986. Explanation-based generalization: a unifying view. Machine Learning, 1:47-80.
8. Neumann, G. 1994a. Application of explanation-based learning for efficient processing of constraint based grammars. In Proceedings of the Tenth IEEE Conference on Artificial Intelligence for Applications, pages 208-215, San Antonio, Texas, March.
9. Neumann, G. 1994b. A Uniform Computational Model for Natural Language Parsing and Generation. Ph.D. thesis, Universit~t des Saarlandes, Germany, Europe, November.
10. Neumann, G. and G. van Noord. 1994. Reversibility and self-monitoring in natural language generation. In Tomek Strzalkowski, editor, Reversible Grammar in Natural Language Processing. Kluwer, pages 59-96.
11. Pollard, C. and I. M. Sag. 1994. Head-Driven Phrase Structure Grammar. Center for the Study of Language and Information Stanford.
12. Rayner, M. 1988. Applying explanation-based generalization to natural language processing. In Proceedings of the International Conference on Fifth Generation Computer Systems, Tokyo.
13. Rayner, M. and D. Carter. 1996. Fast parsing using pruning and grammar specialization. In 34th Annual Meeting of the Association for Computational Linguistics, Morristown, New Jersey.
14. Samuelsson, C. 1994. Fast Natural-Language Parsing Using Explanation-Based Learning. Ph.D. thesis, Swedish Institute of Computer Science, Kista, Sweden, Europe.
15. Samuelsson, C. 1995a. An efficient algorithm for surface generation. In Proceedings of the 14th International Joint Conference on Artificial Intelligence, pages 1414-1419, Montreal, Canada.
16. Samuelsson, C. 1995b. Example-based optimization of surface-generation tables. In Proceedings of Recent Advances in Natural Language Processing, Velingrad, Bulgaria, Europe.
17. Samuelsson, C. and M. Rayner. 1991. Quantitative evaluation of explanation-based learning as an optimization tool for a large-scale natural language system. In IJCAI-91, pages 609-615, Sydney, Australia.
18. Shemtov, H. 1996. Generation of Paraphrases from Ambiguous Logical Forms. In Proceedings of the 16th International Conference on Computational Linguistics (COLING), pages 919-924, Kopenhagen, Denmark, Europe.
19. Shieber, S. M. 1993. The problem of logical-form equivalence. Computational Linguistics, 19:179-190.
20. Srinivas, B. and A. Joshi. 1995. Some novel applications of explanation-based learning to parsing lexicalized tree-adjoining grammars. In 33th Annual Meeting of the Association for Computational Linguistics, Cambridge, MA.
21. van Harmelen, F. and A. Bundy. 1988. Explanation-based generalization=partial evaluation. Artificial Intelligence, 36:401-412.