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A Method of Link Prediction Based on Betweenness

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Book cover Computational Social Networks (CSoNet 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9197))

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Abstract

Link prediction in complex networks has attracted increasing attention of researchers in many domains. The prediction methods are usually used to find missing information, identify spurious interactions, and reconstruct networks. Inspired by the rich-get-richer mechanism, we propose a novel index on the basis of betweenness. Extensive experiments show that the proposed method performs well on some networks. Especially, on the Adjnoun network and Florida network, it outperforms some mainstream link prediction baselines, such as CN Index, AA Index and RA Index.

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Author information

Authors and Affiliations

  1. College of Science, National University of Defense Technology, Changsha, 410073, China

    Pengyuan Zhang, Jianping Li, Enming Dong & Qi Liu

Authors
  1. Pengyuan Zhang
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  2. Jianping Li
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  3. Enming Dong
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  4. Qi Liu
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Corresponding author

Correspondence to Pengyuan Zhang .

Editor information

Editors and Affiliations

  1. Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, USA

    My T. Thai

  2. Towsen University, Towson, Maryland, USA

    Nam P. Nguyen

  3. Chinese Academy of Sciences, Beijing, China

    Huawei Shen

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© 2015 Springer International Publishing Switzerland

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Zhang, P., Li, J., Dong, E., Liu, Q. (2015). A Method of Link Prediction Based on Betweenness. In: Thai, M., Nguyen, N., Shen, H. (eds) Computational Social Networks. CSoNet 2015. Lecture Notes in Computer Science(), vol 9197. Springer, Cham. https://doi.org/10.1007/978-3-319-21786-4_20

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  • DOI: https://doi.org/10.1007/978-3-319-21786-4_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21785-7

  • Online ISBN: 978-3-319-21786-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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