An Effective Hypergraph Clustering in Multi-Stage Data Mining of Traditional Chinese Medicine Syndrome Differentiation
| Autor: | Zhang Ming-wei, Zhang Bin, Wei Wei-Jie, Wang Bo |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Clustering high-dimensional data
Hypergraph Association rule learning Computer science business.industry Graph theory Similarity measure computer.software_genre Machine learning Data set CURE data clustering algorithm Consensus clustering Data mining Artificial intelligence Greedy algorithm business Cluster analysis computer |
| Zdroj: | ICDM Workshops |
| DOI: | 10.1109/icdmw.2006.27 |
| Popis: | Traditional Chinese Medicine is mysterious for its special diagnosis and treatment. In TCM, Syndrome differentiation is the method of recognizing and diagnosing diseases or body imbalances in TCM. In this paper, we first give a hierarch model of differentiation syndrome in Traditional Chinese Medicine According to the model data mining procedure is designed to complete it. Given special data mining schema and character of high-dimensional data sets, we introduce hypergraph based on greedy algorithm in cluster and similarity measure during clustering stage. Finally, the experiment shows that the hypergraph clustering is correct and efficient, which in return could be important for association rules and diagnosis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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