Name
Abstract | ||
|---|---|---|
Outlier mining is an important part in data mining. In this paper, through the research of causes and detection methods of outlier, combined with the perspective of granular computing, we firstly present a general guiding principle of outlier mining that is granulation viewpoint, which shows that choosing reasonable granularity before granulation plays a very crucial role in outlier mining. Then we show a unified process frame diagram based on granular computing for outlier detection. Finally, a new algorithm based on granulation viewpoint for outlier detection is given. We argue that this paper can provide the practical reference value for the selection, improvement and the innovation of outlier detection method. And outlier mining based on granular computing will offer a kind of new thinking of research and analytic method for the future research topics and the challenges of the outlier mining. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/GRC.2008.4664651 | GrC |
Keywords | Field | DocType |
outlier detection method,granularity,granular computing,data mining,outlier mining,granulation,algorithm design and analysis,outlier detection,unified process | Data mining,Anomaly detection,Algorithm design,Computer science,Unified Process,Outlier,Granular computing,Artificial intelligence,Granularity,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-2513-6 | 0 | 0.34 |
References | Authors | |
9 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuang Liu | 1 | 0 | 0.34 |
| Ji-yi Wang | 2 | 17 | 8.05 |
| Guolin Xing | 3 | 2 | 0.70 |