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Published in: The Journal of Supercomputing 5/2020

28-08-2018

Establishment of herbal prescription vector space model based on word co-occurrence

Authors: Shouqiang Chen, Yang Chen, Feng Yuan, Xiaowei Chang

Published in: The Journal of Supercomputing | Issue 5/2020

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Abstract

This paper analyzes the establishment of vector space model (VSM) of herbal prescription. Currently, VSM has been frequently used in knowledge acquisition and information retrieval. However, as VSM ignores the association between words, the herbal prescription can only be expressed with single Chinese herb as unit and the potential semantic information in herbal prescription cannot be fully reflected, which limits the clustering result of herbal prescription. This study investigates the significance of word co-occurrence for the research on the formulation theory of herbal prescription, verifies the association between the major function of herbal prescription between word co-occurrence and proposes the word co-occurrence-based VSM and expression method of second-order weighted eigenvalues. It can be concluded that the proposed method can achieve better effect in clustering analysis of herbal prescription comparing traditional VSM-based expression method.

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Metadata
Title
Establishment of herbal prescription vector space model based on word co-occurrence
Authors
Shouqiang Chen
Yang Chen
Feng Yuan
Xiaowei Chang
Publication date
28-08-2018
Publisher
Springer US
Published in
The Journal of Supercomputing / Issue 5/2020
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2559-3

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