- The KDD (Knowledge Discovery in Databases) paradigm is a step by step process for finding interesting patterns in large amounts of data. Data mining is one step in the process. T...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
The paper presents the parameter-less implementation of an evolutionary-based search. It does not need any predefined control parameters values, which are usually used for geneti...
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
This poster session examines a probabilistic approach to distributed information retrieval using a Logistic Regression algorithm for estimation of collection relevance. The algori...