Outlier detection research is currently focusing on the development of new methods and on improving the computation time for these methods. Evaluation however is rather heuristic,...
Erich Schubert, Remigius Wojdanowski, Arthur Zimek...
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Abstract. Outlier detection is concerned with discovering exceptional behaviors of objects. Its theoretical principle and practical implementation lay a foundation for some importa...
Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W...
The discovery of objects with exceptional behavior is an important challenge from a knowledge discovery standpoint and has attracted much attention recently. In this paper, we pre...