Complementary structures in disjoint science literatures
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
An interactive system for finding complementary literatures: a stimulus to scientific discovery
Artificial Intelligence - Special issue on scientific discovery
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Text mining for finding functional community of related genes using TCM knowledge
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Context-Based Web Ontology Service for TCM Information Sharing
ICWS '05 Proceedings of the IEEE International Conference on Web Services
Chinese Word Segmentation and Named Entity Recognition: A Pragmatic Approach
Computational Linguistics
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Using statistical and knowledge-based approaches for literature-based discovery
Journal of Biomedical Informatics
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Guest editorial: Integrative data mining in systems biology: from text to network mining
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Computational methods for Traditional Chinese Medicine: A survey
Computer Methods and Programs in Biomedicine
Survey of Text Mining II: Clustering, Classification, and Retrieval
Survey of Text Mining II: Clustering, Classification, and Retrieval
Methodological Review: Extracting interactions between proteins from the literature
Journal of Biomedical Informatics
Building Clinical Data Warehouse for Traditional Chinese Medicine Knowledge Discovery
BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01
Building a semantically annotated corpus of clinical texts
Journal of Biomedical Informatics
Artificial Intelligence in Medicine
Text mining for clinical chinese herbal medical knowledge discovery
DS'05 Proceedings of the 8th international conference on Discovery Science
Ontology development for unified traditional Chinese medical language system
Artificial Intelligence in Medicine
Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text
Artificial Intelligence in Medicine
Journal of Biomedical Informatics
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Journal of Biomedical Informatics
Hi-index | 0.00 |
Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions.