We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Mining multimedia data is one of the most important issues in data mining. In this paper, we propose an online one-pass algorithm to mine the set of frequent temporal patterns in ...
Continuous queries applied over nonterminating data streams usually specify windows in order to obtain an evolving –yet restricted– set of tuples and thus provide timely result...
Abstract-- Privacy preservation in data mining demands protecting both input and output privacy. The former refers to sanitizing the raw data itself before performing mining. The l...
We propose a space-efficient scheme for summarizing multidimensional data streams. Our sketch can be used to solve spatial versions of several classical data stream queries effici...
John Hershberger, Nisheeth Shrivastava, Subhash Su...