Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018)

A Study on Knowledge Discovery based on Big Data Background of Visceral Manifestation Theory in Huangdi’s Internal Classic of Medicine

Authors
Yanda She
Corresponding Author
Yanda She
Available Online December 2018.
DOI
10.2991/icedem-18.2018.83How to use a DOI?
Keywords
Big Data; Database; Visceral Manifestation Theory; Knowledge discovery; Huangdi’s Internal Classic of Medicine
Abstract

This paper, under the background of big data, combines both the theory of "Huangdi undefined Internal Classic" and the pharmaceutical annotation theory of Huangdi’s Internal Classic of Medicine with database, devises applied program, and probes into knowledge discovery, thus obtaining the theme distribution of the theory of liver storage image, and providing a methodological reference for the study of traditional Chinese medicine classical theory.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
December 2018
ISBN
978-94-6252-642-6
ISSN
2352-5398
DOI
10.2991/icedem-18.2018.83How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yanda She
PY  - 2018/12
DA  - 2018/12
TI  - A Study on Knowledge Discovery based on Big Data Background of Visceral Manifestation Theory in Huangdi’s Internal Classic of Medicine
BT  - Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018)
PB  - Atlantis Press
SP  - 328
EP  - 330
SN  - 2352-5398
UR  - https://doi.org/10.2991/icedem-18.2018.83
DO  - 10.2991/icedem-18.2018.83
ID  - She2018/12
ER  -