ProMine: A Text Mining Solution for Concept Extraction and Filtering

Saira Gillani () and Andrea Kő
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Saira Gillani: Corvinus University of Budapest

A chapter in Corporate Knowledge Discovery and Organizational Learning, 2016, pp 59-82 from Springer

Abstract: 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.

Keywords: Business Process; Domain Ontology; Compound Word; Knowledge Element; Semantic Similarity Measure (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-28917-5_3

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