This paper defines and discusses a new problem in the area of subspace clustering. It defines the problem of mining closed subspace clusters. This new concept allows for the culli...
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...