With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
Existing algorithms for mining association patterns often rely on the support-based pruning strategy to prune a combinatorial search space. However, this strategy is not effective ...
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...
In order to allow for the analysis of data sets including numerical attributes, several generalizations of association rule mining based on fuzzy sets have been proposed in the li...
Effective information systems require the existence of explicit process models. A completely specified process design needs to be developed in order to enact a given business proce...
Laura Maruster, A. J. M. M. Weijters, Wil M. P. va...
Data visualization plays a crucial role in identifying interesting patterns in exploratory data analysis. Its use is, however, made difficult by the large number of possible data p...
Clipping is the process of transforming a real valued series into a sequence of bits representing whether each data is above or below the average. In this paper, we argue that clip...
Anthony J. Bagnall, Chotirat (Ann) Ratanamahatana,...