Abstract
In this paper, we propose a novel network clustering algorithm, called CPSCAN for detecting the communities of citation network based on the temporal feature. Firstly, with combining temporal interval and citation path, a structural similarity model and a clustering algorithm is proposed. Then we propose a new modularity for measuring the quality of clustering on citation network. In empirical evaluation, we compare our method with existing methods on real world datasets. The experimental results demonstrates our algorithm has better performance on citation network than others methods.
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Acknowledgment
The National Natural Science Foundation of China under Grant No. 61402213, 61472070, the Fundamental Research Funds for the Central Universities No. N150408001-3, N150404013
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© 2016 Springer International Publishing Switzerland
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Zhang, B., Nie, T., Shen, D., Kou, Y., Yu, G., Zhou, Z. (2016). A Graph Clustering Algorithm for Citation Networks. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9932. Springer, Cham. https://doi.org/10.1007/978-3-319-45817-5_37
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DOI: https://doi.org/10.1007/978-3-319-45817-5_37
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