Abstract
This paper introduces a maximum entropy method to Discourse Coherence Modeling (DCM). Different from the state-of-art supervised entity-grid model and unsupervised cohesion-driven model, the model we proposed only takes as input lexicon features, which increases the training speed and decoding speed significantly. We conduct an evaluation on two publicly available benchmark data sets via sentence ordering tasks, and the results confirm the effectiveness of our maximum entropy based approach in DCM.
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Tu, M., Zhou, Y., Zong, C.: Enhancing grammatical cohesion: generating transitional expressions for SMT. In: 52nd Annual Meeting of the ACL, Baltimore, USA (2014)
Prasad, R., Bunt, H.: Semantic relations in discourse: the current state of ISO 24617-8. In: Proceedings 11th Joint ACL-ISO Workshop on Interoperable Semantic Annotation (ISA-11), pp. 80–92 (2015)
Lin, Z.H., Liu, C., Ng, H.W., Kan, M.Y.: Combining coherence models and machine translation evaluation metrics for summarization evaluation. In: Proceedings of the ACL. Association for Computational Linguistics, Jeju, pp. 1006–1014 (2012)
Halliday, M.A.K., Hasan, R.: Text and context: aspects of language in a social-semiotic perspective. Sophia Linguistica 6, 4–91 (1980). Working Papers in Linguistics Tokyo
De Beaugrande, R.A., Dressler, W.U.: Introduction to text linguistics. Longman, London (1981)
Mann, W.C., Thompson, S.A.: Rhetorical structure theory: Toward a functional theory of text organization. Text 8(3), 243–281 (1988)
Cristea, D., Ide, N., Romary, L.: Veins theory: A model of global discourse cohesion and coherence. In: Proceedings of the 17th international conference on Computational linguistics. Association for Computational Linguistics, vol. 1, pp. 281–285 (1998)
Grosz, B.J., Joshi, A.K., Weinstein, S., et al.: Centering: A Framework for Modelling the Local Coherence of Discourse. Computational Linguistics 21(2), 203–225 (1995)
Kamp, H., Kamp, H.: Discourse Representation Theory: What it is and Where it Ought to Go. Natural Language at the Computer 320(1), 84–111 (1988)
Barzilay, R., Lapata, M.: Modeling local coherence: an entity-based approach. Computational Linguistics 34(1), 1–34 (2008)
Lin, Z.H., Ng, H.T., Kan, M.Y.: Automatically evaluating text coherence using discourse relations. In: Proceedings of the ACL. Association for Computational Linguistics, Portland, pp. 997–1006 (2011)
Feng, V.W., Hirst, G.: Extending the entity-based coherence model with multiple ranks. In: Proceedings of the EACL. Association for Computational Linguistics, Avignon, pp. 315–324 (2012)
Eisner, M., Charniak, E.: Extending the entity grid with entity-specific features. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, short papers, vol. 2. Association for Computational Linguistics, pp. 125–129 (2011)
Guinaudeau, C., Strube, M.: Graph-based Local Coherence Modeling. In: ACL, vol. 1, pp. 93–103 (2013)
Louis, A., Nenkova, A.: A coherence model based on syntactic patterns. In: Proceedings of the EMNLP-CNLL. Association for Computational Linguistics, Jeju, pp. 1157–1168 (2012)
Xu, F., Zhu, Q., Zhou, G., et al.: Cohesion-driven Discourse Coherence Modeling. Journal of Chinese Information 28(3), (2014)
Li, J., Hovy, E.: A model of coherence based on distributed sentence representation. In: Proceedings of the EMNLP (2014)
Rosenfeld, R.: A maximum entropy approach to adaptive statistical language modelling. Computer Speech & Language 10(3), 187–228 (1996)
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© 2015 Springer International Publishing Switzerland
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Lin, R., Yang, M., Liu, S., Li, S., Zhao, T. (2015). A Maximum Entropy Approach to Discourse Coherence Modeling. In: Li, J., Ji, H., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2015. Lecture Notes in Computer Science(), vol 9362. Springer, Cham. https://doi.org/10.1007/978-3-319-25207-0_1
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DOI: https://doi.org/10.1007/978-3-319-25207-0_1
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