Abstract
Processes in public administration are complex and changing fast, according to the changes in the regulatory environment. Public servants have to face with the challenge of getting a job role specific knowledge, which is embedded into the processes or available in other unstructured sources, like in public policies. Even though much of government regulations may now available in digital form, due to their complexity and diversity, identifying the ones relevant to a particular context is a non-trivial task. Our paper will discuss a text mining solution to extract, organize and preserve knowledge embedded in organizational processes to enrich the organizational knowledge base in a systematic and controlled way, support employees to easily acquire their job role specific knowledge. The solution has been tested for the case of an agricultural service at public authority. The context of the case is sampling in controlling food safety and quality.
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Gillani, S.A., Kő, A. (2014). Process-Based Knowledge Extraction in a Public Authority: A Text Mining Approach. In: Kő, A., Francesconi, E. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2014. Lecture Notes in Computer Science, vol 8650. Springer, Cham. https://doi.org/10.1007/978-3-319-10178-1_8
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DOI: https://doi.org/10.1007/978-3-319-10178-1_8
Publisher Name: Springer, Cham
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