Autors: Rozeva, A. G., Ivavov, M.P., Tsankova, R.S.
Title: Business modelling for generation of knowledge from explicit data
Keywords: Knowledge generation, business model, text mining, data mining, administration management, categorization, clustering

Abstract: The aim of the paper is to present a framework for designing business model for knowledge generation from explicit data on “good” administrative management practices. Knowledge discovery demands the availability and access to high volumes of data. There is such data collected in databases and files in different formats. Knowledge extraction is performed by statistical and machine learning mining methods of text mining and data mining. The proposed framework for business model design consists of structure and knowledge models. The two models refer to the text transformation and the knowledge extraction phases respectively. Structure model implements text mining methods for converting the text documents into structured objects. These objects form a data mining structure that is the source for the knowledge discovery models. They are oriented to descriptive and predictive modelling tasks which concern document clustering and categorization. The business model framework is trained on sou

References

    Issue

    Proceedings of the First International Symposium on Business Modeling and Software Design BMSD'11, pp. 114-128, 2011, Bulgaria, SciTePress, ISBN 978-989-8425-68-3

    Copyright Publisher

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus