IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Descriptive Question Answering with Answer Type Independent Features
Yeo-Chan YOONChang-Ki LEEHyun-Ki KIMMyung-Gil JANGPum Mo RYUSo-Young PARK
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2012 Volume E95.D Issue 7 Pages 2009-2012

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Abstract

In this paper, we present a supervised learning method to seek out answers to the most frequently asked descriptive questions: reason, method, and definition questions. Most of the previous systems for question answering focus on factoids, lists or definitional questions. However, descriptive questions such as reason questions and method questions are also frequently asked by users. We propose a system for these types of questions. The system conducts an answer search as follows. First, we analyze the user's question and extract search keywords and the expected answer type. Second, information retrieval results are obtained from an existing search engine such as Yahoo or Google. Finally, we rank the results to find snippets containing answers to the questions based on a ranking SVM algorithm. We also propose features to identify snippets containing answers for descriptive questions. The features are adaptable and thus are not dependent on answer type. Experimental results show that the proposed method and features are clearly effective for the task.

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© 2012 The Institute of Electronics, Information and Communication Engineers
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