UID:
almahu_9949697902802882
Format:
1 online resource (252 p.)
Edition:
1st ed.
ISBN:
1-280-98320-5
,
9786613754813
,
0-12-398519-6
Series Statement:
Elsevier insights
Content:
Recognized as an essential component of Chinese culture, Traditional Chinese Medicine (TCM) is both an ancient medical system and one still used widely in China today. TCM's independently evolved knowledge system is expressed mainly in the Chinese language and the information is frequently only available through ancient classics and confidential family records, making it difficult to utilize. The major concern in TCM is how to consolidate and integrate the data, enabling efficient retrieval and discovery of novel knowledge from the dispersed data. Computational approaches such as data minin
Note:
Description based upon print version of record.
,
Front Cover; Modern Computational Approaches To Traditional Chinese Medicine; Copyright Page; Contents; Preface; List of Contributors; 1 Overview of Knowledge Discovery in Traditional Chinese Medicine; 1.1 Introduction; 1.2 The State of the Art of TCM Data Resources; 1.2.1 Traditional Chinese Medical Literature Analysis and Retrieval System; 1.2.2 Figures and Photographs of Traditional Chinese Drug Database; 1.2.3 Database of Chinese Medical Formulae; 1.2.4 Database of Chemical Composition from Chinese Herbal Medicine; 1.2.5 Clinical Medicine Database
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1.2.6 TCM Electronic Medical Record Database1.3 Review of KDTCM Research; 1.3.1 Knowledge Discovery for CMF Research; 1.3.2 Knowledge Discovery for CHM Research; 1.3.2.1 KDD for the Research of CHM Characteristics; 1.3.2.2 KDD for the Research of CHM Chemical Compositions; 1.3.3 Knowledge Discovery for Research of TCM Syndrome; 1.3.4 Knowledge Discovery for TCM Clinical Diagnosis; 1.4 Discussions and Future Directions; 1.5 Conclusions; References; 2 Integrative Mining of Traditional Chinese Medicine Literature and MEDLINE for Functional Gene Networks; 2.1 Introduction
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2.2 Connecting TCM Syndrome to Modern Biomedicine by Integrative Literature Mining2.3 Related Work on Biomedical Literature Mining; 2.4 Name Entity and Relation Extraction Methods; 2.4.1 Bubble-Bootstrapping Method; 2.4.1.1 Pattern Definition; 2.4.1.2 Bubble-Bootstrapping Algorithm; 2.4.2 Relation Weight Computing; 2.5 MeDisco/3S System; 2.6 Results; 2.6.1 Functional Gene Networks; 2.6.2 Functional Analysis of Genes from Syndrome Perspective; 2.7 Conclusions; References; 3 MapReduce-Based Network Motif Detection for Traditional Chinese Medicine; 3.1 Introduction; 3.2 Related Work
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3.3 MapReduce-Based Pattern Finding3.3.1 MRPF Framework; 3.3.2 Neighbor Vertices Finding and Pattern Initialization; 3.3.3 Pattern Extension; 3.3.4 Frequency Computing; 3.4 Application to Prescription Compatibility Structure Detection; 3.4.1 Motifs Detection Results; 3.4.2 Performance Analysis; 3.5 Conclusions; References; 4 Data Quality for Knowledge Discovery in Traditional Chinese Medicine; 4.1 Introduction; 4.2 Key Data Quality Dimensions in TCM; 4.2.1 Representation Granularity; 4.2.2 Representation Consistency; 4.2.3 Completeness; 4.3 Methods to Handle Data Quality Problems
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4.3.1 Handling Representation Granularity4.3.2 Handling Representation Consistency; 4.3.3 Handling Completeness; 4.4 Conclusions; References; 5 Service-Oriented Data Mining in Traditional Chinese Medicine; 5.1 Introduction; 5.2 Related Work; 5.2.1 Traditional Data Mining Software; 5.2.2 Data Mining Systems for Specific Field; 5.2.3 Distributed Data Mining Platform; 5.2.4 The Spora Demo; 5.3 System Architecture and Data Mining Service; 5.3.1 Hierarchical Structure; 5.3.1.1 Resource Layer; 5.3.1.2 Component Layer; 5.3.1.3 Service Layer; 5.3.1.4 Application Layer
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5.3.2 Service Operator Organization
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English
Additional Edition:
ISBN 0-323-28272-5
Additional Edition:
ISBN 0-12-398510-2
Language:
English
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