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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Optimization and Generation of Knowledge Model for Supporting Technology Innovation
verfasst von : Seungsu Jun, Seungryong Lee, Munbong Shin
Erschienen in: Future Information Technology
Verlag: Springer Berlin Heidelberg
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In information society, there are now worldwide economic network that are expanding prodigiously. There could be argued that social structure is in dire need of supporting technology innovation. This paper seeks to analysis and how to generate of knowledge model that supporting policy making of technology innovation. We let the user focus on some interested parts a whole decision making and to analysis using case and how to generate knowledge model and network through advanced semantic mining and formal language. Knowledge model is created to topic network that compositing driven keyword through text mining from natural language in document. And we show that the way of analyzing knowledge model and automatically generating feature keyword and relation properties into topic networks. In order that we analyze the semantic relationship and knowledge properties using CTL(Computational Tree Logic) on organized topic map and Kripke structure.