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Link Prediction Based on Supernetwork Model and Attention Mechanism

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Knowledge and Systems Sciences (KSS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 949))

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Abstract

To make full use of various types of data in link prediction, we proposed a link prediction method (SA, the abbreviation of supernetwork and attention mechanism) with two parts: information extraction and similarity measurement. Information is extracted on the basis of supernetwork for its multilayered, aggregative and other characteristics. In this part, we defined the operating unit for the flexibility and depth of information extraction. With the help of information extraction, we can get different types of subnetworks, which can be used in the similarity measurement. The similarity measurement part is inspired by the idea of attention mechanism: the allocation of attention might be different according to the difference of both subnetworks and nodes. After studying three types of relationships in the supernetwork, we proposed a similarity index (SimSA) combined three relationship types. To test the new method, we compared SA with famous CN and RA in the real data set of Douban, a popular social network site, and verified the application value of the new method.

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Acknowledgement

This work is supported by the National Natural Science Foundation of China under Grants 71573247, 91746106.

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Authors and Affiliations

  1. Institutes of Science and Development, CAS, Beijing, 100190, China

    Yuxue Chi & Yijun Liu

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yuxue Chi & Yijun Liu

Authors
  1. Yuxue Chi
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  2. Yijun Liu
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Corresponding author

Correspondence to Yijun Liu .

Editor information

Editors and Affiliations

  1. School of Economics and Management, Tsinghua University, Beijing, China

    Jian Chen

  2. Graduate School of Business Sciences, University of Tsukuba, Bunkyō, Tokyo, Tokyo, Japan

    Yuji Yamada

  3. Faculty of Business Sciences, University of Tsukuba, Tokyo, Japan

    Mina Ryoke

  4. Institute of Systems Science, CAS Academy of Mathematics and Systems Sciences, Beijing, China

    Xijin Tang

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Chi, Y., Liu, Y. (2018). Link Prediction Based on Supernetwork Model and Attention Mechanism. In: Chen, J., Yamada, Y., Ryoke, M., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2018. Communications in Computer and Information Science, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-3149-7_15

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  • DOI: https://doi.org/10.1007/978-981-13-3149-7_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3148-0

  • Online ISBN: 978-981-13-3149-7

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