IQA: Interactive SPARQL Query Construction in Semantic Question Answering Systems

Tracking #: 1953-3166

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Hamid Zafar
Mohnish Dubey
Jens Lehmann
Elena Demidova

Responsible editor: 
Guest Editors Knowledge Graphs 2018

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Semantic Question Answering (QA) systems automatically interpret users' questions expressed in a natural language in terms of formal semantic queries. This process involves uncertainty, such that the resulting semantic queries do not always accurately match the users' intent, especially for more complex and less common questions. In this article, we aim to empower users in guiding QA systems towards the intended semantic queries by means of interaction. We introduce a probabilistic framework that enables seamlessly incorporating user interaction and feedback directly in the question answering process. We propose and evaluate a model for the interaction process. Our evaluation shows that using this framework, even a small number of user interactions can lead to significant improvements in the performance of QA systems.
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