Introduction to the EXCITEMENT project: towards an open platform for EXploring customer interactions through textual entailMENT

Wasserblat, Moshe; Daya, Ezra; Hurvitz, Eyal; Gorodetsky, Maya; Volsky, Dmitri; Dagan, Ido; Adler, Meni; Steren, Asher; Pado, Sebastian; Noh, Tae-Gil; Zeller, Britta; Neumann, Günter; Eichler, Kathrin; Wang, Rui; Fidanza, Gabriele; Gianforme, Giorgio; Meisdrock, Matthias; Magnini, Bernardom; Bentivogli, Luisa; Zanoli, Roberto; Lavelli, Alberto

Introduction to the EXCITEMENT project: towards an open platform for EXploring customer interactions through textual entailMENT

Moshe Wasserblat, Ezra Daya, Eyal Hurvitz, Maya Gorodetsky, Dmitri Volsky, Ido Dagan, Meni Adler, Asher Steren, Sebastian Pado, Tae-Gil Noh, Britta Zeller, Günter Neumann, Kathrin Eichler, Rui Wang, Gabriele Fidanza, Giorgio Gianforme, Matthias Meisdrock, Bernardom Magnini, Luisa Bentivogli, Roberto Zanoli, Alberto Lavelli

Identifying semantic inferences between text units is a major underlying language processing task, needed in practically all text understanding applications. While such inferences are broadly needed, there are currently no generic semantic “engines” or platforms for broad textual inference. The primary scientific motivation for the EXCITEMENT project is to change this ineffective state of affairs and to offer an encompassing open source platform for textual inference. On the industrial side, EXCITEMENT is focused on the text analytics and speech analytics markets and follows the increasing demand for automatically analyzing customer interactions, which today cross multiple channels including speech, email, chat and social media.