Classification-based Contextual Preferences
Shachar Mirkin, Ido Dagan, Lili Kotlerman and Idan Szpektor
In: TextInfer 2011, 31/7/2011, Edinburgh, UK.
This paper addresses context matching in textual inference. We formulate the task under the Contextual Preferences framework which broadly captures contextual aspects of inference. We propose a generic classiﬁcationbased scheme under this framework which coherently attends to context matching in inference and may be employed in any inferencebased task. As a test bed for our scheme we use the Name-based Text Categorization (TC) task. We deﬁne an integration of Contextual Preferences into the TC setting and present a concrete self-supervised model which instantiates the generic scheme and is applied to address context matching in the TC task. Experiments on standard TC datasets show that our approach outperforms the state of the art in context modeling for Name-based TC.