Journal of Guangdong University of Technology ›› 2017, Vol. 34 ›› Issue (03): 30-35.doi: 10.12052/gdutxb.170026

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Research on using information flow and HowNet to build big data semantic sharing channel

Mao Li-na1, Li Wei-hua2   

  1. 1. Department of Mechanical and Electrical Engineering, Guangdong Industry Polytechnic, Guangzhou 510300, China;
    2. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2017-01-19 Online:2017-05-09 Published:2017-05-09

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Abstract:

In addition to the huge amount of data, wide range of data, different information structure, grammatical and semantic conflicts, highly heterogeneous and dynamic, big data is difficult to share. In order to share the semantic information in big data, there must be a sharing mechanism with dynamic, heterogeneous and large-scale features to enable users to share semantic information of big data. Information Flow theory, also called Channel Theory, as well as HowNet, have been analyzed. Combine them provide us bases of big data semantic understanding. The idea of building the big data semantics sharing channel based both on the information flow theory and Hownet is present. Information resources classify ontology, society ontology and channel ontology act as the kernel of the semantic sharing. Build the big data semantic sharing channel by infomorphisms. Professional information sharing as case study has carried on the preliminary practice. The experiment results show the effectiveness of the constructed channel. Combining information flow theory and HowNet technology can form a useful big data semantic sharing channel.

Key words: big data, semantics, information flow, channel

CLC Number: 

  • TP311

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