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Knowledge Graph Embedding for Link Prediction and Triplet Classification

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Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data (CCKS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 650))

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Abstract

The link prediction (LP) and triplet classification (TC) are important tasks in the field of knowledge graph mining. However, the traditional link prediction methods of social networks cannot directly apply to knowledge graph data which contains multiple relations. In this paper, we apply the knowledge graph embedding method to solve the specific tasks with Chinese knowledge base Zhishi.me. The proposed method has been successfully used in the evaluation task of CCKS2016. Hopefully, it can achieve excellent performance.

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Notes

  1. 1.

    https://keras.io.

  2. 2.

    https://code.google.com/archive/p/word2vec/.

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Acknowledgement

This work has been partially funded by the National Basic Reseach Program of China (2014CB340404) and the IBM SUR (2015) grant.

Author information

Authors and Affiliations

  1. Tongji University, Shanghai, 201804, People’s Republic of China

    E. Shijia, Shengbin Jia & Yang Xiang

  2. IBM China Systems and Technology Laboratory, Shanghai, 201203, People’s Republic of China

    Zilian Ji

Authors
  1. E. Shijia
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  2. Shengbin Jia
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  3. Yang Xiang
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  4. Zilian Ji
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Corresponding author

Correspondence to Yang Xiang .

Editor information

Editors and Affiliations

  1. Zhejiang University, Zhejiang, China

    Huajun Chen

  2. Rensselaer Polytechnic Institute, Troy, New York, USA

    Heng Ji

  3. Chinese Academy of Sciences, Beijing, China

    Le Sun

  4. Google Research, Mountain View, California, USA

    Haixun Wang

  5. Wuhan University, Wuhan, Hubei, China

    Tieyun Qian

  6. East China University of Science and Technology, Shanghai, China

    Tong Ruan

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© 2016 Springer Nature Singapore Pte Ltd.

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Shijia, E., Jia, S., Xiang, Y., Ji, Z. (2016). Knowledge Graph Embedding for Link Prediction and Triplet Classification. In: Chen, H., Ji, H., Sun, L., Wang, H., Qian, T., Ruan, T. (eds) Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data. CCKS 2016. Communications in Computer and Information Science, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-10-3168-7_23

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  • DOI: https://doi.org/10.1007/978-981-10-3168-7_23

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3167-0

  • Online ISBN: 978-981-10-3168-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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