The goal of the DATCHA project is to perform knowledge extraction from very large databases of WEB chat conversations between operators and clients in customer contact centers. Extracting knowledge from chat corpus is a challenging research issue. Simply applying traditional text mining tools is clearly sub-optimal as it takes into account neither the interaction dimension nor the particular nature of this language which shares properties of both spoken and written language. The DATCHA project will address scientific issues including intra-conversation analysis through a deep semantic analysis (syntactic, semantic, discursive and structural analysis) and inter-conversation analysis (definition of semantic and discursive similarity between conversations). It will propose innovative solutions in various use-cases including analytics report generation, conversation success prediction on the basis of criteria defined by operational units, and online conversation solving.
- Project meeting at IRIT
- Paper accepted at Sigdial'16
- Paper accepted at LREC'16
- Project presented at ANR
- Project kickoff at AMU
- Mailing list creation
- The Datcha project is funded!
Latest publications from or related to the project:
- Benoit Favre et al., "Apprentissage d'agents conversationnels pour la gestion de relations clients", Traitement Automatique du Langage Naturel (Demo), 2017.
- Jihen Karoui et al., "Exploring the Impact of Pragmatic Phenomena on Irony Detection in Tweets: A Multilingual Corpus Study", To appear in the proceedings of EACL 2017 (long paper), 2017.
- Alexis Nasr et al., "Syntactic parsing of chat language in contact center conversation corpus", 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue, 2016.
- Frederic Bechet (frederic.bechet at lif.univ-mrs.fr)
- Aix-Marseille Université, LIF/CNRS, Parc Scientifique et Technologique de Luminy, 163 avenue de Luminy - Case 901, F-13288 Marseille Cedex 9, France.
Last updated on 2017-07-13