Abstract
Cross-network user identification is a technique to infer the potential links among the shared user entities across multiple networks. However, existing methods mainly rely on a small set of seed users which might not get enough evidence for identification. In this paper, we propose a cross-network user identification model based on two-phase expansion. On one hand, in order to effectively solve the cold start problem, we propose a global seed expansion method to expand the seed set. On the other hand, we propose a local search range expansion method with the aim to ensure higher accuracy at a lower time cost. Experiments demonstrate the effectiveness of our proposed model.
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Acknowledgment
This work is supported by the National Key R&D Program of China (2018YFB1003404), the National Natural Science Foundation of China (61672142, U1435216) and the Program of China Scholarships Council (201806085016).
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Kou, Y., Li, X., Feng, S., Shen, D., Nie, T. (2019). A Cross-Network User Identification Model Based on Two-Phase Expansion. In: Ni, W., Wang, X., Song, W., Li, Y. (eds) Web Information Systems and Applications. WISA 2019. Lecture Notes in Computer Science(), vol 11817. Springer, Cham. https://doi.org/10.1007/978-3-030-30952-7_39
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DOI: https://doi.org/10.1007/978-3-030-30952-7_39
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