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ProMine: A Text Mining Solution for Concept Extraction and Filtering

In: Corporate Knowledge Discovery and Organizational Learning

Author

Listed:
  • Saira Gillani

    (Corvinus University of Budapest)

  • Andrea Kő

    (Corvinus University of Budapest)

Abstract

Due to the on-going economic crisis, the management of organizational knowledge is becoming more and more important. This knowledge resides in organizational processes. The extraction of this hidden knowledge from the business processes and the usage of this knowledge for domain ontology development is a major challenge. This chapter presents ProMine, a text mining ontology extraction tool that extracts deep representations from the business processes. ProMine extracts new domain related concepts and proposes a new filtering mechanism based on a new hybrid similarity measure to filter most relevant concepts. The tool is evaluated through a case study of the insurance domain. The results showed that ProMine performance is good and it generates many new concepts against each business process.

Suggested Citation

  • Saira Gillani & Andrea Kő, 2016. "ProMine: A Text Mining Solution for Concept Extraction and Filtering," Knowledge Management and Organizational Learning, in: András Gábor & Andrea Kő (ed.), Corporate Knowledge Discovery and Organizational Learning, pages 59-82, Springer.
    • Handle: RePEc:spr:kmochp:978-3-319-28917-5_3
    DOI: 10.1007/978-3-319-28917-5_3
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    Cited by:

    1. Andrea Kő & Réka Vas & Tibor Kovács & Ildikó Szabó, 2019. "Knowledge Creation from the Perspective of the Supply Chain. The Role of ICT," Society and Economy, Akadémiai Kiadó, Hungary, vol. 41(3), pages 311-329, September.

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