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Node Classification in Social Network via a Factor Graph Model

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Advances in Knowledge Discovery and Data Mining (PAKDD 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7818))

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Abstract

This paper attempts to addresses the task of node classification in social networks. As we know, node classification in social networks is an important challenge for understanding the underlying graph with the linkage structure and node features. Compared with the traditional classification problem, we should not only use the node features, but also consider about the relationship between nodes. Besides, it is difficult to cost much time and energy to label every node in the large social networks. In this work, we use a factor graph model with partially-labeled data to solve these problems. Our experiments on two data sets (DBLP co-author network, Weibo) with multiple small tasks have demonstrated that our model works much better than the traditional classification algorithms.

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Author information

Authors and Affiliations

  1. Shenzhen Key Laboratory of Information Science and Technology, Graduate School at Shenzhen, Tsinghua University, P.R. China

    Huan Xu, Yujiu Yang & Wenhuang Liu

  2. Noah’s Ark Laboratory, Huawei Technologies Co., Ltd., Shenzhen, P.R. China

    Liangwei Wang

Authors
  1. Huan Xu
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  2. Yujiu Yang
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  3. Liangwei Wang
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  4. Wenhuang Liu
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Editor information

Editors and Affiliations

  1. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  2. Dept. of Computer Science and Information Engineering, Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  3. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, P.O. Box 123, 2007, Sydney, NSW, Australia

    Longbing Cao  & Guandong Xu  & 

  4. Asian Office of Aerospace Research and Development (AOARD), Air Force Office of Scientific Research (AFOSR), Air Force Research Laboratory USA, Osaka University, 7-23-17 Roppongi, 106-0032, Minato-ku, Tokyo, Japan

    Hiroshi Motoda

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Xu, H., Yang, Y., Wang, L., Liu, W. (2013). Node Classification in Social Network via a Factor Graph Model. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37453-1_18

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  • DOI: https://doi.org/10.1007/978-3-642-37453-1_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37452-4

  • Online ISBN: 978-3-642-37453-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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