ACTraversal: ranking crowdsourced commonsense assertions and certifications

Authors:
Tao-Hsuan Chang;Yen-Ling Kuo;Jane Yung-jen Hsu
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University, Taiwan
Venue:
PRIMA'11 Proceedings of the 14th international conference on Agents in Principle, Agents in Practice
Year:
2011

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Abstract

Building commonsense knowledge bases is a challenging undertaking. While we have witnessed the successful collection of large amounts of commonsense knowledge by either automatic text mining or games with a purpose (GWAP), such data are of limited precision. Verifying data is typically done with repetition, which works better for very large data sets. Our research proposes a novel approach to data verification by coupling multiple data collection methods. This paper presents ACTraversal, a graph traversal algorithm for ranking data collected from GWAP and text mining. Experiments on aggregating data from two GWAPs, i.e. Virtual Pets and Top10, with two text mining tools, i.e. SEAL and Google Distance, showed significant improvements.