Autors: Rozeva, A. G.
Title: Extraction of knowledge models from e-governance documents
Keywords: knowledge model, text analysis, text mining, knowledge engineering, knowledge base, ontology, e-Governance

Abstract: Significant volumes of text in unstructured form are available in the web and in different administrative and corporate digital stores. The analysis of textual data by specific information technologies as text mining results in patterns which describe relationships, dependencies or associations among terms or documents. This is analytical approach for knowledge engineering. The content of a knowledge base is represented by knowledge models. The paper presents an approach for the design of knowledge models from different text analysis tasks. The framework involves knowledge engineering and ontological representation. It is implemented on text corpus with papers on e-Governance. The resultant knowledge models are presented. Ontology is instantiated for the formal representation of the knowledge models and sample logic queries for retrieving knowledge from the knowledge base are shown.

References

    Issue

    Challenges, solutions, knowledge models in e-governance, pp. 94-104, 2013, Bulgaria, Technical University – Sofia, ISBN 978-619-167-049-9

    Copyright Publisher

    Вид: монография/части от монография, публикация в реферирано издание, индексирана в Google Scholar