Question answering system for dialogues: A new taxonomy of opinion questions

Abstract

Question analysis is an important task in Question Answering Systems (QAS). To perform this task, the system must procure fine-grained information about the question types. This information is defined by the question taxonomy. In the literature, factual question taxonomies were the object of many research works. However, opinion question taxonomies did not get the same attention because they are more complicated. Besides, most QAS were focusing on monologal texts, while dialogues have rarely been explored by information retrieval tools. In this paper, we investigate the use of dialogue data as an information source for opinion QAS. Hence, we propose a new opinion question taxonomy in the context of an Arabic QAS for political debates and we propose then an approach to classify these questions. Obtained results were relevant with a precision of around 91.13% for the opinion classes' classification. © 2013 Springer-Verlag Berlin Heidelberg.