@article{li2013comparable,
author = {Li, Shasha and Lin, Chin-Yew and Song, Young-In and Li, Zhoujun},
title = {Comparable Entity Mining from Comparative Questions},
year = {2013},
month = {July},
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. In this paper, we present a novel way to automatically mine comparable entities from comparative questions that users posted online to address this difficulty. To ensure high precision and high recall, we develop a weakly supervised bootstrapping approach for comparative question identification and comparable entity extraction by leveraging a large collection of online question archive. The experimental results show our method achieves F1-measure of 82.5 percent in comparative question identification and 83.3 percent in comparable entity extraction. Both significantly outperform an existing state-of-the-art method. Additionally, our ranking results show highly relevance to user's comparison intents in web.},
url = {http://approjects.co.za/?big=en-us/research/publication/comparable-entity-mining-from-comparative-questions/},
pages = {1498-1509},
journal = {IEEE Transactions on Knowledge and Data Engineering},
volume = {25},
number = {7},
}