Centrality Research on the Traditional Chinese Medicine Network*

Zhang Dezheng; Gao Lixin; Zhang Huansheng; Liu Jianming

1st International ICST Workshop on Knowledge Discovery and Data Mining

Research Article

Centrality Research on the Traditional Chinese Medicine Network*

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/wkdd.2008.2662,
    author={Zhang Dezheng and Gao Lixin and Zhang Huansheng and Liu Jianming},
    title={Centrality Research on the Traditional Chinese Medicine Network*},
    proceedings={1st International ICST Workshop on Knowledge Discovery and Data Mining},
    publisher={ACM},
    proceedings_a={WKDD},
    year={2010},
    month={5},
    keywords={},
    doi={10.4108/wkdd.2008.2662}
}

Zhang Dezheng
Gao Lixin
Zhang Huansheng
Liu Jianming
Year: 2010
Centrality Research on the Traditional Chinese Medicine Network*
WKDD
ACM
DOI: 10.4108/wkdd.2008.2662

Zhang Dezheng¹^,*, Gao Lixin¹, Zhang Huansheng²^,*, Liu Jianming¹

1: School of Information Engineering, University of Science and Technology Beijing, Beijing, China 100083
2: Department of Computer, Hebei Engineering And Technical College, Cangzhou, Hebei 061001

*Contact email: zdzchina@126.com, why05118@sina.com

Abstract

Aiming at the complex data in the Traditional Chinese Medicine, a new way is proposed in this paper that data mining of complex relations to find out the potential information among different medicine objects. We turned the Traditional Chinese Medicine knowledge network into graph by using information from ontology, then adopted centrality algorithm to analyze and process this graph, and finally mined valuable medicine knowledge. As the result of the verification test, this algorithm shows very good practicability.

Published: 2010-05-16
Publisher: ACM
Modified: 2010-05-16

: http://dx.doi.org/10.4108/wkdd.2008.2662

Centrality Research on the Traditional Chinese Medicine Network*

Abstract

About EAI

Community

Publish with EAI