Abstract-- In recent years, data streams have become ubiquitous because of advances in hardware and software technology. The ability to adapt conventional mining problems to data s...
Abstract. We investigate the problem of finding frequent patterns in a continuous stream of transactions. It is recognized that the approximate solutions are usually sufficient and...
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transact...