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The Recognition of Multiple Virtual Identities Association Based on Multi-agent System

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Agents and Data Mining Interaction (ADMI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8316))

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Abstract

The recognition of multiple virtual identities association has aroused extensive attention, which can be widely used in author identification, forum spammer detection and other fields. We focus on the features of authors behavior on the dynamic data. This paper applies multi-agent system to the authors information mining fields and proposes a recognition model based on multi-agent system: MVIA-MAS. We cluster the author information in each time slice in parallel and then use association rule mining to find the target author groups, in which the multiple virtual identities are considered associated. Experiments show that the model has a better overall performance.

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Acknowledgements

We warmly thank Wentang Tan for his guidance. This work was funded under National Science and Technology Support Program (NO.2012BAH08B01).

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Correspondence to Le Li .

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Li, L., Xiao, W., Dai, C., Xu, J., Ge, B. (2014). The Recognition of Multiple Virtual Identities Association Based on Multi-agent System. In: Cao, L., Zeng, Y., Symeonidis, A., Gorodetsky, V., Müller, J., Yu, P. (eds) Agents and Data Mining Interaction. ADMI 2013. Lecture Notes in Computer Science(), vol 8316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55192-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-55192-5_4

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  • Print ISBN: 978-3-642-55191-8

  • Online ISBN: 978-3-642-55192-5

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