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Object Clustering in Linked Data Using Centrality

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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

Large-scale linked data is becoming a challenge to many Semantic Web tasks. While clustering of graphs has been deeply researched in network science and machine learning, not many researches are carried on clustering in linked data. To identify meta-structures in large-scale linked data, the scalability of clustering should be considered. In this paper, we propose a scalable approach of centrality-based clustering, which works on a model of Object Graph derived from RDF graph. Centrality of objects is calculated as indicators for clustering. Both relational and linguistic closeness between objects are considered in clustering to produce coherent clusters.

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Notes

  1. 1.

    SWCC: http://data.semanticweb.org/.

  2. 2.

    JAME: http://dbtune.org/jamendo/.

  3. 3.

    LMDB: http://linkedmdb.org/.

  4. 4.

    Gephi: https://gephi.org/users/download/.

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Acknowledgement

The work was supported by the National High-Tech Research and Development (863) Program of China (No. 2015AA015406) and the Open Project of Jiangsu Key Laboratory of Data Engineering and Knowledge Service (No. DEKS2014KT002).

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Southeast University, Nanjing, China

    Xiang Zhang & Erjing Lin

  2. College of Software Engineering (Suzhou), Southeast University, Suzhou, China

    Yulian Lv

Authors
  1. Xiang Zhang
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  2. Yulian Lv
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  3. Erjing Lin
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Corresponding author

Correspondence to Xiang Zhang .

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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Zhang, X., Lv, Y., Lin, E. (2016). Object Clustering in Linked Data Using Centrality. 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_17

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  • DOI: https://doi.org/10.1007/978-981-10-3168-7_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3167-0

  • Online ISBN: 978-981-10-3168-7

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