Focusing on multi-document personal name disambiguation, this paper develops an agglomerative clustering approach to resolving this problem. We start from an analysis of pointwise mutual information between feature and the ambiguous name, which brings about a novel weight computing method for feature in clustering. Then a trade-off measure between within-cluster compactness and among-cluster separation is proposed for stopping clustering. After that, we apply a labeling method to find representative feature for each cluster. Finally, experiments are conducted on word-based clustering in Chinese dataset and the result shows a good effect.
REF explored a novel feature weight computing method in clustering.
Clustering Technique in Multi-Document Personal Name Disambiguation
ACL-IJCNLP: Student Research Workshop papers
Computer Science