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Detecting Question Intention Using a K-Nearest Neighbor Based Approach

Abstract : The usage of question answering systems is increasing daily. People constantly use question answering systems in order to find the right answer for different kinds of information, but the abundance of available data has made the process of obtaining relevant information challenging in terms of processing and analyzing it. Many questions classification techniques have been proposed with the aim of helping in understanding the actual intent of the user’s question. In this research, we have categorized different question types through introducing question type syntactical patterns for detecting question intention. In addition, a k-nearest neighbor based approach has been developed for question classification. Experiments show that our approach has a good level of accuracy in identifying different question types.
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Alaa Mohasseb, Mohamed Bader-El-Den, Mihaela Cocea. Detecting Question Intention Using a K-Nearest Neighbor Based Approach. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.101-111, ⟨10.1007/978-3-319-92016-0_10⟩. ⟨hal-01821311⟩

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