Paper: A Probabilistic Co-Bootstrapping Method for Entity Set Expansion

ACL ID C14-1215
Title A Probabilistic Co-Bootstrapping Method for Entity Set Expansion
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

Entity Set Expansion (ESE) aims at automatically acquiring instances of a specific target category. Unfortunately, traditional ESE methods usually have the expansion boundary problem and the semantic drift problem. To resolve the above two problems, this paper proposes a probabilistic Co-Bootstrapping method, which can accurately determine the expansion boundary using both the positive and the discriminant negative instances, and resolve the semantic drift problem by effectively maintaining and refining the expansion boundary during bootstrapping iterations. Experimental results show that our method can achieve a competitive performance.