Name
Abstract | ||
|---|---|---|
When therapy using interferon medication for chronic hepatitis patients, various conceptual knowledge/rules will benefit for giving a treatment. The paper describes our work on cooperatively using various data mining agents including GDT-RS, learning with ordered information (LOI), and peculiarity oriented mining (POM) in a spiral discovery process with the multi-phase such as pre-processing, rule mining, and post-processing, for multi-aspect analysis of the hepatitis data and meta learning. GDT-RS is an inductive learning system for discovering decision rules. LOI discovers ordering rules and important features. POM finds peculiarity data/rules. Our methodology and experimental results show that the perspective of medical doctors will be changed from a single type of experimental data analysis towards a holistic view, by using our multi-aspect mining approach. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1142/S0219622009003478 | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING |
Keywords | Field | DocType |
Data mining, multi-aspect analysis, hepatitis data, spiral discovery process | Decision rule,Data mining,Aspect mining,Experimental data,Rule mining,Artificial intelligence,Business process discovery,Mathematics,Machine learning,K-optimal pattern discovery | Journal |
Volume | Issue | ISSN |
8 | 3 | 0219-6220 |
Citations | PageRank | References |
3 | 0.41 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muneaki Ohshima | 1 | 170 | 11.93 |
| Ning Zhong | 2 | 2907 | 300.63 |
| Juzhen Dong | 3 | 214 | 17.05 |
| Hideto Yokoi | 4 | 198 | 17.11 |