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Managing corporate memory on the semantic web

Author

Listed:
  • Nitesh Khilwani

    (Loughborough University)

  • J. A. Harding

    (Loughborough University)

Abstract

Corporate memory (CM) is the total body of data, information and knowledge required to deliver the strategic aims and objectives of an organization. In the current market, the rapidly increasing volume of unstructured documents in the enterprises has brought the challenge of building an autonomic framework to acquire, represent, learn and maintain CM, and efficiently reason from it to aid in knowledge discovery and reuse. The concept of semantic web is being introduced in the enterprises to structure information in a machine readable way and enhance the understandability of the disparate information. Due to the continual popularity of the semantic web, this paper develops a framework for CM management on the semantic web. The proposed approach gleans information from the documents, converts into a semantic web resource using resource description framework (RDF) and RDF Schema and then identifies relations among them using latent semantic analysis technique. The efficacy of the proposed approach is demonstrated through empirical experiments conducted on two case studies.

Suggested Citation

  • Nitesh Khilwani & J. A. Harding, 2016. "Managing corporate memory on the semantic web," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 101-118, February.
  • Handle: RePEc:spr:joinma:v:27:y:2016:i:1:d:10.1007_s10845-013-0865-4
    DOI: 10.1007/s10845-013-0865-4
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    References listed on IDEAS

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    1. Christian Bizer & Tom Heath & Tim Berners-Lee, 2009. "Linked Data - The Story So Far," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 5(3), pages 1-22, July.
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    Cited by:

    1. Zhaoguang Xu & Yanzhong Dang & Peter Munro & Yuhang Wang, 2020. "A data-driven approach for constructing the component-failure mode matrix for FMEA," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 249-265, January.
    2. Yuval Cohen & Gonen Singer, 2021. "A smart process controller framework for Industry 4.0 settings," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1975-1995, October.
    3. Peter Chhim & Ratna Babu Chinnam & Noureddin Sadawi, 2019. "Product design and manufacturing process based ontology for manufacturing knowledge reuse," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 905-916, February.

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