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A Probabilistic Method for Linking BI Provenances to Open Knowledge Base

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Brain Informatics and Health (BIH 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9919))

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Abstract

Owing the explosive growth of unstructured cognitive big data, provenances become a core issue in Brain informatics. In order to construct a open and sharing knowledge graph about cognitive big data, Brain informatics provenances cannot be isolated. All entities, which were extracted from biomedical literatures, web documents, information systems, etc., should be linked to open knowledge bases, such as DBpedia. However, the entity ambiguity is a key obstacle with the linking task. This paper proposes a probabilistic method for linking BI provenances to open knowledge base. Both the popularity knowledge and context knowledge are considered to solve the entity ambiguity. The experimental results shows the proposed method is effective.

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Acknowledgments

The work is supported by National Key Basic Research Program of China (2014CB744605), National Natural Science Foundation of China (61272345), Research Supported by the CAS/SAFEA International Partnership Program for Creative Research Teams, the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (25330270).

Author information

Authors and Affiliations

  1. Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, 100024, China

    Jing Wang, Yongchuan Yu, Jianzhuo Yan, Jianhui Chen & Zhongcheng Zhao

  2. College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100024, China

    Jing Wang, Yongchuan Yu, Jianzhuo Yan & Jianhui Chen

  3. International WIC Institute, Beijing University of Technology, Beijing, China

    Jianhui Chen & Dongsheng Wang

  4. Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing, China

    Jianhui Chen

  5. Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China

    Jianhui Chen

  6. Institute of Intelligent Transport System, School of Computer Science and Engineering, Jiangsu University of Science of Technology, Zhenjiang, 212003, China

    Dongsheng Wang

Authors
  1. Jing Wang
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  2. Yongchuan Yu
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  3. Jianzhuo Yan
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  4. Jianhui Chen
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  5. Zhongcheng Zhao
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  6. Dongsheng Wang
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Corresponding author

Correspondence to Jing Wang .

Editor information

Editors and Affiliations

  1. George Mason University, Fairfax, Virginia, USA

    Giorgio A. Ascoli

  2. Department of Modeling, Analysis and Theory, Allen Institute for Brain Science, Seattle, Washington, USA

    Michael Hawrylycz

  3. University of Nebraska Omaha, Omaha, Nebraska, USA

    Hesham Ali

  4. Information Science and Technology, University of Nebraska Omaha, Omaha, Nebraska, USA

    Deepak Khazanchi

  5. College of Information Sciences and Technology, University of Nebraska Omaha, Omaha, Nebraska, USA

    Yong Shi

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Wang, J., Yu, Y., Yan, J., Chen, J., Zhao, Z., Wang, D. (2016). A Probabilistic Method for Linking BI Provenances to Open Knowledge Base. In: Ascoli, G., Hawrylycz, M., Ali, H., Khazanchi, D., Shi, Y. (eds) Brain Informatics and Health. BIH 2016. Lecture Notes in Computer Science(), vol 9919. Springer, Cham. https://doi.org/10.1007/978-3-319-47103-7_36

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  • DOI: https://doi.org/10.1007/978-3-319-47103-7_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47102-0

  • Online ISBN: 978-3-319-47103-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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