- R. Banchs, Ryuichiro Higashinaka, W. Minker, J. Mariani, D. Traum, Miroslav Vodolán, Filip Jurcícek, Ondřej Dušek, David Nilsson, Magnus Sahlgren, Jussi Karlgren, Zhou Yu, Ziyu Xu, A. Black, Alexander I. Rudnicky, M. Kaleem, Omar Alobadi, James O’Shea, Keeley A. Crockett, D. Novick, Adriana I. Camacho, I. Gris, Laura M. Rodriguez, B. AbuShawar, E. Atwell, Luis Fernando D'Haro, G. D. Duplessis, Vincent Letard, Anne-Laure Ligozat, S. Rosset, Haizhou Li. 2016. RE-WOCHAT : Workshop on Collecting and Generating Resources for Chatbots and Conversational Agents-Development and Evaluation Workshop Programme ( May 28. Abstract: This paper presents a dataset collected from natural dialogs which enables to test the ability of dialog systems to learn new facts from user utterances throughout the dialog. This interactive learning will help with one of the most prevailing problems of open domain dialog system, which is the sparsity of facts a dialog system can reason about. The proposed dataset, consisting of 1900 collected dialogs, allows simulation of an interactive gaining of denotations and questions explanations from users which can be used for the interactive learning.
