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.
- Demo of conversation annotations
- Project meeting at Orange Labs
- Papers accepted at EACL'17, and TALN'17
- Project meeting at IRIT
- Paper accepted at Sigdial'16 and LREC'16
Latest publications from or related to the project:
- Nicholas Asher et al., "Manuel d'annotation en actes de dialogue pour le corpus Datcha", Datcha technical report, 2017.
- 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.
- 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 2017-10-09