Issue No. 07 - July (2013 vol. 25)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2011.210
Shasha Li , National University of Defense Technology, Beijing
Chin-Yew Lin , Microsoft Research Asia, Beijing
Young-In Song , Microsoft Research Asia, Beijing
Zhoujun Li , Beihang University, Beijing
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.
Reliability, Portable media players, Data mining, Equations, Algorithm design and analysis, Cities and towns, Pattern matching, comparable entity mining, Information extraction, bootstrapping, sequential pattern mining
Z. Li, Y. Song, S. Li and C. Lin, "Comparable Entity Mining from Comparative Questions," in IEEE Transactions on Knowledge & Data Engineering, vol. 25, no. , pp. 1498-1509, 2013.