A Chinese expert name disambiguation approach based on spectral clustering with the expert page-associated relationships

Abstract

Aimed at the problems of Chinese experts' name repetition and representation diversity, a Chinese expert name disambiguation approach based on spectral clustering with the expert page-associated relationships is proposed. Firstly, the TF-IDF algorithm is used to calculate the word-based feature weights, and then the cosine similarity algorithm is employed to compute the similarity between the evidence-pages to obtain the initial similarity matrix of expert evidence-pages. Secondly, the expert page-associated relationship features are taken as the semi-supervised constraint information to correct the initial similarity matrix, and next the spectral clustering-based method is used to build expert disambiguation model. Finally, taking the contrast experiments on Chinese expert evidence-page corpus of manually labeled, the result shows that the semi-supervised spectral clustering on Chinese experts' name disambiguation method with the expert page-associated relationships than that without the associated constraint information, the F-value has an average increase of 9.02 %. © 2013 Springer-Verlag.