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International Conference on Brain Informatics

BIH 2016: Brain Informatics and Health pp 181–189Cite as

A Domain-Driven Literature Retrieval Method for Systematic Brain Informatics

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

Abstract

Systematic brain informatics (BI) research depends on a large amount of prior knowledge and scientific literatures are a kind of important knowledge source. However, the increasing number of scientific literatures has led to information overload. For researchers, it is difficult to find appropriate literatures. Developing literature retrieval technologies and systems becomes an important issue during systematic BI researches. However, most of existing literature retrieval technologies optimize query conditions only based on user interests and cannot effectively reflect domain interests. This paper proposes a domain-driven literature retrieval method which adopts the spread activation model to combine the dynamic and static domain models for ranking query results. The proposed method has been applied to the PubMed dataset. The experiment results show the efficiency of our method for retrieving literatures about brain informatics.

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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, 100124, China

    Wenjin Sheng, Hongxia Xu, Jianzhuo Yan, Bin Shi & Hongzhi Kuai

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

    Wenjin Sheng, Hongxia Xu, Jianzhuo Yan & Hongzhi Kuai

  3. International WIC Institute, Beijing University of Technology, Beijing, 100024, China

    Jianhui Chen, Dongsheng Wang & Ningning Wang

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

    Wenjin Sheng, Hongxia Xu, Jianzhuo Yan, Jianhui Chen, Bin Shi, Dongsheng Wang, Hongzhi Kuai & Ningning Wang

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

    Jianhui Chen

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

    Dongsheng Wang

Authors
  1. Wenjin Sheng
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  2. Hongxia Xu
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  3. Jianzhuo Yan
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  4. Jianhui Chen
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  5. Bin Shi
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  6. Dongsheng Wang
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  7. Hongzhi Kuai
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  8. Ningning Wang
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Corresponding author

Correspondence to Wenjin Sheng .

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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Sheng, W. et al. (2016). A Domain-Driven Literature Retrieval Method for Systematic Brain Informatics. 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_18

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  • DOI: https://doi.org/10.1007/978-3-319-47103-7_18

  • Published:

  • 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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