We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept ...
Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice this discovery process should avoid redundancies with existi...
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
Eliciting requirements for a proposed system inevitably involves the problem of handling undesirable information about customer’s needs, including inconsistency, vagueness, redun...
Analyzing the quality of data prior to constructing data mining models is emerging as an important issue. Algorithms for identifying noise in a given data set can provide a good me...
Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Hu...
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...