—This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain o...
Outlier detection has recently become an important problem in many industrial and financial applications. This problem is further complicated by the fact that in many cases, outlie...
Dragoljub Pokrajac, Aleksandar Lazarevic, Longin J...
Finding bursts in data streams is attracting much attention in research community due to its broad applications. Existing burst detection methods suffer the problems that 1) the p...
The environment around us is progressively equipped with various sensors, producing data continuously. The applications using these data face many challenges, such as data stream i...
In this paper we discuss a data mining framework for constructing intrusion detection models. The key ideas are to mine system audit data for consistent and useful patterns of pro...