Comparable Entity Mining from Comparative Questions
IEEE Transactions on Knowledge and Data EngineeringPublished 13 October 2011
Shasha Li, Chin-Yew Lin, Young-In Song, Zhoujun Li
Citations49
SJR quartileQ1
SJR score2.57
SNIP3.30
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TL;DR
A novel way to automatically mine comparable entities from comparative questions that users posted online to address this difficulty is presented and a weakly supervised bootstrapping approach for comparative question identification and comparable entity extraction is developed.
Abstract
Comparing one thing with another is a typical part of human decision making process. However, it is not always easy to know what to compare and what are the alternatives. To address this difficulty, we present a novel way to automatically mine comparable entities from comparative questions that users posted online. To ensure high precision and high recall, we develop a weakly-supervised bootstrapping method for comparative question identification and comparable entity extraction by leveraging a large online question archive. The experimental results show our method achieves F1measure of 82.5 % in comparative question identification and 83.3 % in comparable entity extraction. Both significantly outperform an existing state-of-the-art method. 1
Keywords
Computer Science
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