Abstract
This paper investigates the use of recurrent surface text patterns to represent and index open-domain dialogue utterances for a retrieval system that can be embedded in a conversational agent. This approach involves both the building of a database of such patterns by mining a corpus of written dialogic interactions, and the exploitation of this database in a generalised vector space model for utterance retrieval. It is a corpus-based, unsupervised, parameterless and language-independent process. Our study indicates that the proposed model performs objectively well comparatively to other retrieval models on a task of selection of dialogue examples derived from a large corpus of written dialogues.
This work was funded by the JOKER project (www.chistera.eu/projects/joker).
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References
Ameixa, D., Coheur, L., Redol, R.A.: From subtitles to human interactions: introducing the subtle corpus. Technical report, INESC-ID (2013)
Banchs, R.E., Li, H.: IRIS: a chat-oriented dialogue system based on the vector space model. In: Proceedings of the ACL 2012 Demonstrations, pp. 37–42 (2012)
Charras, F., Dubuisson Duplessis, G., Letard, V., Ligozat, A.L., Rosset, S.: Comparing system-response retrieval models for open-domain and casual conversational agent. In: Workshop on Chatbots and Conversational Agent Technologies (2016)
Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by Gibbs sampling. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pp. 363–370 (2005)
Gandhe, S., Traum, D.R.: Surface text based dialogue models for virtual humans. In: Proceedings of the SIGDIAL (2013)
Gusfield, D.: Algorithms on Strings, Trees and Sequences. Cambridge University Press, Cambridge (1997)
Le, Q.V., Mikolov, T.: Distributed representations of sentences and documents. In: ICML, vol. 14, pp. 1188–1196 (2014)
Lee, C., Jung, S., Kim, S., Lee, G.G.: Example-based dialog modeling for practical multi-domain dialog system. Speech Commun. 51(5), 466–484 (2009)
Lison, P., Tiedemann, J.: OpenSubtitles2016: extracting large parallel corpora from movie and tv subtitles. In: 10th edition of the Language Resources and Evaluation Conference (LREC), Portorož, Slovenia, May 2016
Lowe, R., Pow, N., Serban, I.V., Pineau, J.: The ubuntu dialogue corpus: a large dataset for research in unstructured multi-turn dialogue systems. In: SIGDIAL, p. 285 (2015)
Mooney, C.H., Roddick, J.F.: Sequential pattern mining - approaches and algorithms. ACM Comput. Surv. 45(2), 19:1–19:39 (2013)
Nakov, P., Màrquez, L., Moschitti, A., Magdy, W., Mubarak, H., Freihat, A.A., Glass, J., Randeree, B.: Semeval-2016 task 3: community question answering. In: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp. 525–545 (2016)
Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 311–318 (2002)
Řehůřek, R., Sojka, P.: Software framework for topic modelling with large corpora. In: Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, pp. 45–50. ELRA, Valletta, May 2010
Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, Inc., New York (1986)
Snover, M., Dorr, B., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proceedings of Association for Machine Translation in the Americas, vol. 200 (2006)
Sordoni, A., Galley, M., Auli, M., Brockett, C., Ji, Y., Mitchell, M., Nie, J.Y., Gao, J., Dolan, B.: A neural network approach to context-sensitive generation of conversational responses. CoRR abs/1506.06714 (2015)
Weizenbaum, J.: ELIZA - a computer program for the study of natural language communication between man and machine. Commun. ACM 9(1), 36–45 (1966)
Wong, S.K.M., Ziarko, W., Raghavan, V.V., Wong, P.: On modeling of information retrieval concepts in vector spaces. ACM Trans. Database Syst. 12(2), 299–321 (1987)
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Dubuisson Duplessis, G., Charras, F., Letard, V., Ligozat, AL., Rosset, S. (2017). Utterance Retrieval Based on Recurrent Surface Text Patterns. In: Jose, J., et al. Advances in Information Retrieval. ECIR 2017. Lecture Notes in Computer Science(), vol 10193. Springer, Cham. https://doi.org/10.1007/978-3-319-56608-5_16
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DOI: https://doi.org/10.1007/978-3-319-56608-5_16
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