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.
al REF propose a probabilistic Co-Bootstrapping method to better define the expansion boundary for the web-based entity set expansion.
A Probabilistic Co-Bootstrapping Method for Entity Set Expansion
COLING
Computer Science