In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Measuring the similarity between clusterings is a classic problem with several proposed solutions. In this work we focus on measures based on coassociation of data pairs and perfor...
We present a slicing-based coherence measure for clusters of DTI integral curves. For a given cluster, we probe samples from the cluster by slicing it with a plane at regularly spa...
Evaluating the complexity of business processes during the early stages of their development, primarily during the process modelling phase, provides organizations and stakeholder w...