Abstract
In network embedding, the analysis of the relationship between nodes has a great influence on the link prediction. In this paper, we re-examine the role of network topology in predicting missing links from the perspective of node embedding, and proposed a practical algorithm based on the resource allocation of nodes in network. Experiments on six different data sets show that this method has better performance in link prediction than other methods.
Supported by the Ministry of education of Humanities and Social Science project (17YJCZH260), CERNET Innovation Project (NGII20170901, NGII20180403), the Fund of Fundamental Sichuan Civil-military Integration (18sxb017, 18sxb028).
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Song, X., Yang, C., Zhang, H., Zhao, X., Li, B. (2019). Network Embedding by Resource-Allocation for Link Prediction. In: Nayak, A., Sharma, A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science(), vol 11671. Springer, Cham. https://doi.org/10.1007/978-3-030-29911-8_52
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