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Towards an Enterprise Entity Hub: Integration of General and Enterprise Knowledge

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Semantic Technology (JIST 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9544))

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Abstract

Today’s enterprises possess vast quantities of data generated by their own applications and services across different organisational systems. However, the data tends to be stored in many data-silos with redundant, duplicated, and outdated information. This means that finding the right information and obtaining valuable insights is difficult. To address this problem, we develop the enterprise entity hub that enables users to search, analyse, share, and filter information across large-scale data sources. One of its core components, the base knowledge is used to organise and interlink the organisation’s knowledge model, we then construct a base knowledge through the integration of several data sources, and expand this knowledge by interlinking a set of enterprise content.

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Notes

  1. 1.

    http://dbpedia.org.

  2. 2.

    www.mpi-inf.mpg.de/yago/.

  3. 3.

    www.wikidata.org/.

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Author information

Authors and Affiliations

  1. Software R&D Center, Samsung Electronics Co., Ltd., Samsung-ro 189, Maetan-dong, Yeongtong-gu, Suwon, Gyeonggi, Korea

    Haklae Kim, Jeongsoo Lee & Jungyeon Yang

Authors
  1. Haklae Kim
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  2. Jeongsoo Lee
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  3. Jungyeon Yang
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Corresponding author

Correspondence to Haklae Kim .

Editor information

Editors and Affiliations

  1. Southeast University, Nanjing, China

    Guilin Qi

  2. Osaka University, Ibaraki, Japan

    Kouji Kozaki

  3. The University of Aberdeen, Aberdeen, United Kingdom

    Jeff Z. Pan

  4. Zhongnan Hospital of Wuhan University, Wuhan, China

    Siwei Yu

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Kim, H., Lee, J., Yang, J. (2016). Towards an Enterprise Entity Hub: Integration of General and Enterprise Knowledge. In: Qi, G., Kozaki, K., Pan, J., Yu, S. (eds) Semantic Technology. JIST 2015. Lecture Notes in Computer Science(), vol 9544. Springer, Cham. https://doi.org/10.1007/978-3-319-31676-5_22

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  • DOI: https://doi.org/10.1007/978-3-319-31676-5_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31675-8

  • Online ISBN: 978-3-319-31676-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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