We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
: By considering sentences selected by a query-biased sentence extraction model from the top-retrieved documents, we create a personalised information space which is characterised ...
Anastasios Tombros, Joemon M. Jose, Ian Ruthven, R...
In this paper we discuss algorithms for clustering words into classes from unlabelled text using unsupervised algorithms, based on distributional and morphological information. We...
Hua et al. have proposed a stable and efficient tracking algorithm called “K-means tracker”[2, 3, 5]. This paper describes an adaptive non-target cluster center selection met...
One of the advantages in virtualized computing clusters compared to traditional shared HPC environments is their ability to accommodate user-specific system customization. Howeve...