MedC: A Literature Analysis System for Chinese Medicine Research

Xin Li*, Yu Tong, Wen Wang

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Citations (Scopus)

Abstract

Chinese medicine research documents a significant amount of knowledge. However, compared to Western medicine, there are limited studies that take advantage of and summarize findings based on the Chinese medicine literature. This paper builds a literature analysis system based on information extraction and visualization technologies, which allow users to select and analyze a subset of Chinese medicine literature. The system provides complex search functionalities and makes a set of analyses (summary statistics on medicine/disease/acupuncture points, medicine co-occurrence analysis, and acupuncture point analysis) available to support Chinese medicine scholars and alleviate their workload. The system may facilitate Chinese medicine research and theorization.
Original languageEnglish
Title of host publicationSmart Health
Subtitle of host publicationInternational Conference, ICSH 2015
EditorsXiaolong Zheng, Daniel Dajun Zeng, Hsinchun Chen, Scott J. Leischow
PublisherSpringer International Publishing 
Pages311-320
ISBN (Electronic)9783319291758
ISBN (Print)9783319291741
DOIs
Publication statusPublished - Nov 2015
EventInternational Conference for Smart Health (ICSH 2015) - University of Arizona, Phoenix, United States
Duration: 17 Nov 201518 Nov 2015

Publication series

NameLecture Notes in Computer Science
Volume9545
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference for Smart Health (ICSH 2015)
PlaceUnited States
CityPhoenix
Period17/11/1518/11/15

Research Keywords

  • Chinese medicine
  • Literature analysis
  • Text mining
  • Visualization

Fingerprint

Dive into the research topics of 'MedC: A Literature Analysis System for Chinese Medicine Research'. Together they form a unique fingerprint.

Cite this