Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
In this paper, we develop a mixed-size placement tool, Dragon2005, to solve large scale placement problems effectively. A top-down hierarchical approach based on min-cut partition...
Traditionally, distributed computing problems have been solved by partitioning data into chunks able to be handled by commodity hardware. Such partitioning is not possible in case...
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
—Software clustering is a method for increasing software system understanding and maintenance. Software designers, first use MDG graph to model the structure of software system. ...