A Spatio-Temporal Association Rule (STAR) describes how objects move between regions over time. Since they describe only a single movement between two regions, it is very difficu...
As technology advances we encounter more available data on moving objects, which can be mined to our benefit. In order to efficiently mine this large amount of data we propose an ...
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns in time se...