In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...
The unsupervised nature of cluster analysis means that objects can be clustered in many different ways. This means that different clustering algorithms can lead to vastly different...
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
Abstract. This paper proposes a new knowledge-based method for clustering metagenome short reads. The method incorporates biological knowledge in the clustering process, by means o...
Gianluigi Folino, Fabio Gori, Mike S. M. Jetten, E...
We describe the use of component architecture in an area to which this approach has not been classically applied, the area of cluster system software. By "cluster system soft...
Narayan Desai, Rick Bradshaw, Ewing L. Lusk, Ralf ...