Name
Abstract | ||
|---|---|---|
In this paper we study in a general setting the notion of outliered patterns as intentional knowledge of outliers and algorithms to mine those patterns. Our contributions consist of a model for defining outliered patterns with the help of categorical and behavioral similarities of outliers, and efficient algorithms for mining knowledge sets of distance-based outliers and outliered patterns. Our algorithms require only very limited domain knowledge, and no classified information. We also present an empirical study to show the feasibility of our algorithms. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/IDEAS.2003.1214910 | SEVENTH INTERNATIONAL DATABASE ENGINEERING AND APPLICATIONS SYMPOSIUM, PROCEEDINGS |
Keywords | Field | DocType |
outlier detection,knowledge sets,categorical,similarity,behavioral similarity,outliered patterns | Anomaly detection,Data mining,Data modeling,Computer science,Categorical variable,Artificial intelligence,Cluster analysis,Empirical research,Domain knowledge,Outlier,Database,Knowledge modeling,Machine learning | Conference |
Citations | PageRank | References |
6 | 0.50 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhixiang Chen | 1 | 396 | 33.28 |
| Jian Tang | 2 | 526 | 148.30 |
| Ada Wai-Chee Fu | 3 | 4646 | 417.59 |