Conventional clustering methods typically assume that each data item belongs to a single cluster. This assumption does not hold in general. In order to overcome this limitation, w...
Andreas P. Streich, Mario Frank, David A. Basin, J...
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
Clustering on multi-type relational data has attracted more and more attention in recent years due to its high impact on various important applications, such as Web mining, e-comm...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip...
Software developers have long known that project success requires a robust understanding of both technical and social linkages. However, research has largely considered these inde...
Anita Sarma, Larry Maccherone, Patrick Wagstrom, J...