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Elsevifer Insights provides high quality specialized content， across a range of disc，iplines including Iife sciences，pliysical sciences， social scicnces，engineering，compuLing， and flnance.Through fast-track publicalion，Elscvier Insights offers the reader cutting-edge inforniation，available in eBook or print format.．
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Preface1 Overview of Knowledge Discovery in Traditional Chinese Medicine1.1 Introduction1.2 The State of the Art of TCM Data Resources1.2.1 Traditional Chinese Medical Literature Analysis and Retrieval System1.2.2 Figures and Photographs of Traditional Chinese Drug Database1.2.3 Database of Clunese Medical Formulae1.2.4 Database of Chemical Composition from Chinese Herbal Medicine1.2.5 Clinical Medicine Database1.2.6 TCM Electronic Medical Record Database1.3 Review of KDTCM Research1.3.1 Knowledge Discovery for CMF Research1.3.2 Knowledge Discovery for CHM Research1.3.3 Knowledge Discovery for Research of TCM Syndrome1.3.4 Knowledge Discovery for TCM Clinical Diagnosis1.4 Discussions and Future Directions1.5 Conclusions2 Integrative Mining of Traditional Clunese Medicine Literature and MEDLINE for Functional Gene Networks2.1 Introduction2.2 Connecting TCM Syndrome to Modern Biomedicine by Integrative Literature Mining2.3 Related Work on Biomedical Literature Mining2.4 Name Entity and Relation Extraction Methods2.4.1 Bubble-BootstrappingMethod2.4.2 Relation Weight Computing2.5 MeDisco/3SSystem2.6 Results2.6.1 Functional Gene Networks2.6.2 Functional Analysis of Genes from Syndrome Perspective2.7 Conclusions3 MapReduce-Based Network Motif Detection for Traditional Clunese Medicine3.1 Introduction3.2 Related Work3.3 MapReduce-Based Pattern Finding3.3.1 MRPF Framework3.3.2 Neighbor Vertices Finding and Pattern Initialization3.3.3 Pattern Extension3.3.4 FrequencyComputing3.4 Application to Prescription Compatibility Structure Detection3.4.1 Motifs Detection Results3.4.2 PerformanceAnalysis3.5 Conclusions4 Data Quality for Knowledge Discovery in Traditional Chinese Medicine4.1 Introduction4.2 Key Data Quality Dimensions in TCM4.2.1 Representation Granularity4.2.2 RepresentationConsistency4.2.3 Completeness4.3 Methods to Handle Data Quality Problems4.3.1 Handling Representation Granularity4.3.2 Handling Representation Consistency4.3.3 HandlingCompleteness4.4 Conclusions5 Service-Oriented Data Mining in Traditional Chinese Medicine5.1 Introduction5.2 Related Work5.2.1 Traditional Data Mining Software5.2.2 Data Mining Systems for Specific Field5.2.3 Distributed Data Mining Platform5.2.4 The Spora Demo5.3 System Architecture and Data Mining Service5.3.1 Hierarchical Structure5.3.2 Service Operator Organization5.3.3 Userlnteraction and Visualization5.4 Case Studies5.4.1 Case 1: Domain-Driven KDD Support for TCM5.4.2 Case 2: Data Mining Based on Distributed Resources5.4.3 Case 3: Data Mining Process as a Service5.5 Conclusions……6 Semantic E-Science for Traditional Clunese Medicine7 Ontology Development for Unified Traditional Chinese Medical Language System8 Causal Knowledge Modeling for Traditional Chinese Medicine Using OWL 29 Dynamic Subontology Evolution for Traditional Chinese Medicine Web Ontology10 Semantic Association Mining for Traditional Chinese Medicine11 Semantic-Based Database Integration for Traditional Chinese Medicine12 Probabilistic Semantic Relationship Discovery from Traditional Chinese Medical Literature13 Deriving Similarity Graphs from Traditional Chinese Medicine Linked Data on the Semantic Web．
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