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Corporate Knowledge Discovery and Organizational Learning pp 59–82Cite as

ProMine: A Text Mining Solution for Concept Extraction and Filtering

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Part of the book series: Knowledge Management and Organizational Learning ((IAKM,volume 2))

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.

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Notes

  1. 1.

    EUREKA_HU_12-1-2012-0039, supported by the Research and Technology Innovation Fund, New Széchenyi Plan, Hungary.

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Authors and Affiliations

  1. Corvinus University of Budapest, Budapest, Hungary

    Saira Gillani & Andrea Kő

Authors
  1. Saira Gillani
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  2. Andrea Kő
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Correspondence to Saira Gillani .

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Editors and Affiliations

  1. Corvinno Ltd., Budapest, Hungary

    András Gábor

  2. Corvinus University of Budapest, Budapest, Hungary

    Andrea Kő

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Gillani, S., Kő, A. (2016). ProMine: A Text Mining Solution for Concept Extraction and Filtering. In: Gábor, A., Kő, A. (eds) Corporate Knowledge Discovery and Organizational Learning. Knowledge Management and Organizational Learning, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-28917-5_3

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