Scholar search-oriented author disambiguation

Name ambiguity problem brings many challenges to scholar search. This problem has attracted many attentions in research communities, and various disambiguation algorithms combined with different citation features are proposed. However, there is still significant room for improvement. In this paper, we propose an unsupervised two-steps method to deal with the name disambiguation problems as an end user makes a scholar search. In the first step, the returned author´s citations are blocked by using co-authorship relation, and then in second step, these blocks are merged by the classical hierarchical agglomerative clustering method. We test various linkage criteria and pairwise distances during hierarchical clustering, and find the best components to disambiguate citations. Also, we propose some approaches to improve the disambiguation performance in each step. According to experiments, our method outperforms 15% a best state-of-the-art work using the same recognized dataset without the need for any training.