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 %.
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Acknowledgments
This paper is supported by National Nature Science Foundation (No. 61175068), and the Open Fund of Software Engineering Key Laboratory of Yunnan Province (No. 2011SE14), and the Ministry of Education of Returned Overseas Students to Start Research and Fund Projects.
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Tian, W., Shen, T., Yu, Z., Guo, J., Xian, Y. (2013). A Chinese Expert Name Disambiguation Approach Based on Spectral Clustering with the Expert Page-Associated Relationships. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_28
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DOI: https://doi.org/10.1007/978-3-642-38466-0_28
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