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Utterance Retrieval based on Recurrent Surface Text Patterns

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.
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Contributor : Guillaume Dubuisson Duplessis <>
Submitted on : Monday, January 16, 2017 - 10:30:33 AM
Last modification on : Sunday, May 2, 2021 - 3:30:18 AM
Long-term archiving on: : Monday, April 17, 2017 - 12:42:48 PM


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  • HAL Id : hal-01436052, version 1


Guillaume Dubuisson Duplessis, Franck Charras, Vincent Letard, Anne-Laure Ligozat, Sophie Rosset. Utterance Retrieval based on Recurrent Surface Text Patterns. 39th European Conference on Information Retrieval, Apr 2017, Aberdeen, United Kingdom. ⟨hal-01436052⟩



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