There are currently few datasets appropriate for training and evaluating models for non-goal-oriented dialogue systems (chatbots); and equally problematic, there is currently no standard procedure for evaluating such models beyond the classic Turing test.
The aim of our competition is therefore to establish a concrete scenario for testing chatbots that aim to engage humans, and become a standard evaluation tool in order to make such systems directly comparable.
R. Jäschke, A. Hotho, F. Mitzlaff, and G. Stumme. Recommender Systems for the Social Web, volume 32 of Intelligent Systems Reference Library, Springer, Berlin/Heidelberg, (2012)
R. Jäschke, A. Hotho, F. Mitzlaff, and G. Stumme. Recommender Systems for the Social Web, volume 32 of Intelligent Systems Reference Library, Springer, Berlin/Heidelberg, (2012)
R. Jäschke, A. Hotho, F. Mitzlaff, and G. Stumme. Recommender Systems for the Social Web, volume 32 of Intelligent Systems Reference Library, Springer, Berlin/Heidelberg, (2012)
R. Jäschke, A. Hotho, F. Mitzlaff, and G. Stumme. Recommender Systems for the Social Web, volume 32 of Intelligent Systems Reference Library, Springer, Berlin/Heidelberg, (2012)
R. Jäschke, A. Hotho, F. Mitzlaff, and G. Stumme. Recommender Systems for the Social Web, volume 32 of Intelligent Systems Reference Library, Springer, Berlin/Heidelberg, (2012)
A. Hotho, D. Benz, R. Jäschke, and B. Krause (Eds.) Workshop at 18th Europ. Conf. on Machine Learning (ECML'08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'08), (2008)