A bayesian approach to intention-based response generation
The statistical approach to natural language generation of overgeneration-andranking suffers from expensive over generation. This article reports the findings of response classification experiment in the new approach of intention-based classification-andranking. Possible responses are deliberately...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
EuroJournals Publishing, Inc.
2009
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/12647/1/A%20bayesian%20approach%20to%20intention.pdf |
| _version_ | 1825945084143599616 |
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| author | Mustapha, Aida Sulaiman, Md. Nasir Mahmod, Ramlan Selamat, Mohd. Hasan |
| author_facet | Mustapha, Aida Sulaiman, Md. Nasir Mahmod, Ramlan Selamat, Mohd. Hasan |
| author_sort | Mustapha, Aida |
| collection | UPM |
| description | The statistical approach to natural language generation of overgeneration-andranking suffers from expensive over generation. This article reports the findings of response
classification experiment in the new approach of intention-based classification-andranking. Possible responses are deliberately chosen from a dialogue corpus rather than wholly generated, so the approach allows short ungrammatical utterances as long as they satisfy the intended meaning of the input utterance. We hypothesize that a response is relevant when it satisfies the intention of the preceding utterance, therefore this approach highly depends on intentions, rather than syntactic characterization of input utterance. The response classification experiment is tested on a mixed-initiative, transaction dialogue corpus in the theater domain. This article reports a promising start of 73% accuracy in
prediction of response classes in a classification experiment with application of Bayesian networks. |
| first_indexed | 2024-03-06T07:26:00Z |
| format | Article |
| id | upm.eprints-12647 |
| institution | Universiti Putra Malaysia |
| language | English English |
| last_indexed | 2024-03-06T07:26:00Z |
| publishDate | 2009 |
| publisher | EuroJournals Publishing, Inc. |
| record_format | dspace |
| spelling | upm.eprints-126472015-10-23T02:17:16Z http://psasir.upm.edu.my/id/eprint/12647/ A bayesian approach to intention-based response generation Mustapha, Aida Sulaiman, Md. Nasir Mahmod, Ramlan Selamat, Mohd. Hasan The statistical approach to natural language generation of overgeneration-andranking suffers from expensive over generation. This article reports the findings of response classification experiment in the new approach of intention-based classification-andranking. Possible responses are deliberately chosen from a dialogue corpus rather than wholly generated, so the approach allows short ungrammatical utterances as long as they satisfy the intended meaning of the input utterance. We hypothesize that a response is relevant when it satisfies the intention of the preceding utterance, therefore this approach highly depends on intentions, rather than syntactic characterization of input utterance. The response classification experiment is tested on a mixed-initiative, transaction dialogue corpus in the theater domain. This article reports a promising start of 73% accuracy in prediction of response classes in a classification experiment with application of Bayesian networks. EuroJournals Publishing, Inc. 2009 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/12647/1/A%20bayesian%20approach%20to%20intention.pdf Mustapha, Aida and Sulaiman, Md. Nasir and Mahmod, Ramlan and Selamat, Mohd. Hasan (2009) A bayesian approach to intention-based response generation. European Journal of Scientific Research, 32 (4). pp. 477-489. ISSN 1450216X Bayesian statistical decision theory Mathematical optimization Expert systems (Computer science) English |
| spellingShingle | Bayesian statistical decision theory Mathematical optimization Expert systems (Computer science) Mustapha, Aida Sulaiman, Md. Nasir Mahmod, Ramlan Selamat, Mohd. Hasan A bayesian approach to intention-based response generation |
| title | A bayesian approach to intention-based response generation |
| title_full | A bayesian approach to intention-based response generation |
| title_fullStr | A bayesian approach to intention-based response generation |
| title_full_unstemmed | A bayesian approach to intention-based response generation |
| title_short | A bayesian approach to intention-based response generation |
| title_sort | bayesian approach to intention based response generation |
| topic | Bayesian statistical decision theory Mathematical optimization Expert systems (Computer science) |
| url | http://psasir.upm.edu.my/id/eprint/12647/1/A%20bayesian%20approach%20to%20intention.pdf |
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