TITLE:
Adaptive Resonance Theory Based Two-Stage Chinese Name Disambiguation
AUTHORS:
Xin Wang, Yuanchao Liu, Xiaolong Wang, Ming Liu, Bingquan Liu
KEYWORDS:
Name Disambiguation; Adaptive Resonance Theory; Text Clustering; Natural Language Processing
JOURNAL NAME:
International Journal of Intelligence Science,
Vol.2 No.4,
October
30,
2012
ABSTRACT: It’s common that different individuals share the same name, which makes it time-consuming to search information of a particular individual on the web. Name disambiguation study is necessary to help users find the person of interest more readily. In this paper, we propose an Adaptive Resonance Theory (ART) based two-stage strategy for this problem. We get a first-stage clustering result with ART1 model and then merge similar clusters in the second stage. Our strategy is a mimic process of manual disambiguation and need not to predict the number of clusters, which makes it competent for the disambiguation task. Experimental results show that, in comparison with the agglomerative clustering method, our strategy improves the performance by respectively 0.92% and 5.00% on two kinds of name recognition results.