Semantic Web Development for Traditional Chinese Medicine

Tong Yu, Zhejiang University. China.

July. 15th, 2008, IAAI, Chicago, Il.

Outline

• Overview of TCM Semantic Web• Ontology Engineering and Reuse• Semantic Mapping and Integration• Semantic Query, Search and

Navigation• Semantic Graph Mining • Summary

The Semantic Web: “A Giant Graph of Things”

• Based on the Internet and the Web• Formal Semantics

o Use URIs as names for thingso RDF information about things available through HTTP URIso Use RDF statements for semantic links between things

• Global network of databases

Project Background

• Preservation and Modernization of TCM

• Integrative Medicine • Connecting the data• A Student Project

The ultimate vision: Make a connection between TCM and modern medicine

User Scenario

TCM Ontology Platform

• Domain Categorizationo The current TCM ontology contains 15 major

categories for each sub-domain.

• Ontology Structureo A typing system as a concept hierarchyo A semantic network defining the associations between concepts

• Scaleo More than 20,000 classes and 100,000 instances

defined in the current ontology

• Access Controlo layered privilege mechanism that defines users as

reader, editor, checker and administrator.

• Serviceo Web APIs for ontology-based applications.

The 15 Categories Defined in the TCM Ontology

Ajax-based Ontology Viewer and Editor

Ontology Fusion and Reuse

Visualized Mapper: An Eclipse Plugin

Visualized Mapper: The Ajax-based Tool

• http://ec2-67-202-22-44.compute-1.amazonaws.com:8890/demo/mapper/

Semantic Search Portal

Semantic Graph Mining

• We envision that intelligent agents could work on the Semantic Web of structured data, and assist their masters to solve problems, who can o discover important Web resourceso discern latent semantic associationso interpret interesting graph patterns.

• Existing methods of data mining, especially graph mining, can be adopted to implement these intelligent agents.

• We propose a methodology, called Semantic Graph Mining (SGM), for building agents that discover knowledge on the Semantic Web.

TCM Semantic Graph

The Network of Herbs

The Process for Analyzing the Network of Herbs

1.Data Modeling2.Data

Transformation & Integration :

3.Entity Disambiguation

4.Interaction Identification

5.Network Mapping6.Network Analysis

Semantic Graph Resource Importance

• the in-degree centrality CI of a resource is measured by the weighted sum of statements with the resource as object, and the out-degree centrality is measured by the weighted sum of statements with the resource as subject.

Semantic Graph Resource Importance

• The Closeness Centrality of a resource r is defined as the inverse of the sum of the distance from r to all other resources.

Semantic Graph Resource Importance

• The Betweenness Centrality of a resource r is defined as the ratio of shortest paths across the resource in the graph.

Frequent Semantic Subgraph

SG1 SG2

SG3

SG4SG5

Frequent Semantic Subgraph

Pattern Interpretation

Interactive Mining of TCM Knowledge

Conclusion

• We took the first systematic approach to leverage the progress of Biomedical Informatics to address the modernization of TCM.

• Domain experts evaluate the platform’s major technical features as original and productive in Drug Safety and Efficacy analysis.

• This case study demonstrates the Semantic Web’s advantages in representation, integration, and discovery of knowledge with complex domain models.

• Contributes to the Preservation and Modernization of TCM as intangible cultural heritage.

Reference

• TCM Ontology Engineering and Reuseo Y. Mao, et al. Dynamic Sub-Ontology Evolution for Traditional Chinese

Medicine Web Ontology. Journal of Biomedical Informatics, 2008 (In progress)

o Y. Mao et al. Sub-Ontology Based Resource Management for Web-based e-Learning. IEEE Transactions on Knowledge and Data Engineering, 2008 (In Progress)

• Data Mapping and Integrationo Zhao-hui Wu, Hua-jun Chen. 2008. Semantic Grid:Model,

Methodology,and Applications (Monograph). Co-published by Zhejiang University Press and Springer-Verlag GmbH.

o Huajun Chen et al. RDF/RDFS-based Relational Database Integration. ICDE 2006

o Huajun Chen et al.From Legacy Relational Databases to the Semantic Web: an In-Use Application for Traditional Chinese Medicine. ISWC 2006.

Reference

• Semantic Search, Query, and Navigationo Huajun Chen et al. Towards semantic e-science for traditional chinese

medicine. BMC Bioinformatics, 8(Suppl 3):56, 2007.• Knowledge Discovery for TCM

o Yi Feng et al. Knowledge discovery in traditional Chinese medicine: State of the art and perspectives, AI in Medicine, 38(3): 219-236, 2006.

o Xuezhong Zhou et al. Integrative mining of traditional Chinese medicine literature and MEDLINE for functional gene networks. AI in Medicine (2007) 41, 87—104.

• Semantic Graph Miningo Tong Yu et al. Semantic Graph Mining for Biomedical Complex Network

Analysis. WWW ’08 Workshops: HCLS.o Huajun Chen et al. Semantic Graph Mining for Biomedical Complex

Network Analysis. Brief. In Bioinformatics ( In progress).

Thanks for your time!