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Research on Knowledge Fusion Connotation and Process Model

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Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data (CCKS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 650))

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Abstract

The emergence of big-data brings diversified structures and constant growths of knowledge. The objective of knowledge fusion (KF) research is to integrate, discover and exploit valuable knowledge from distributed, heterogeneous and autonomous knowledge sources, which is the necessary prerequisite and effective approach to implement knowledge services. In order to apply KF practice, this paper firstly discusses KF connotations in terms of analysing the relations and differences among various notions, i.e. knowledge fusion, knowledge integration, information fusion and data fusion. Then, based on the knowledge representation method using ontology, this paper investigates several KF implementation patterns and provides two types of dimensional KF process models oriented to demands of knowledge services.

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Notes

  1. 1.

    https://www.w3.org/TR/2012/REC-owl2-primer-20121211/.

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Acknowledgement

This paper is supported by the Chinese NSFC International Cooperation and Exchange Program, Research on Intelligent Home Care Platform based on Chronic Diseases Knowledge Management (71661167007).

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Correspondence to Fei Wang .

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Fan, H., Wang, F., Zheng, M. (2016). Research on Knowledge Fusion Connotation and Process Model. In: Chen, H., Ji, H., Sun, L., Wang, H., Qian, T., Ruan, T. (eds) Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data. CCKS 2016. Communications in Computer and Information Science, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-10-3168-7_18

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  • DOI: https://doi.org/10.1007/978-981-10-3168-7_18

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  • Online ISBN: 978-981-10-3168-7

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