In this paper, we address the problem of semisupervision in the framework of parametric clustering by using labeled and unlabeled data together. Clustering algorithms can take adv...
Cluster systems have been gradually more popular and are being broadly used in a variety of applications. On the other hand, many of those systems are not tolerant to system failu...
Abstract We develop a distance metric for clustering and classification algorithms which is invariant to affine transformations and includes priors on the transformation parameters...
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
Abstract— Visualizing software architecture faces the challenges of both data complexity and visual complexity. This paper presents an approach for visualizing software architect...