Jan 28, 2013 · In this paper, we define a unified distance measure on both link structures and side attributes for clustering. In addition, we propose a novel ...

Abstract. Graph clustering becomes an important problem due to emerging applications involving the web, social networks and bio-informatics.

This paper defines a unified distance measure on both link structures and side attributes for clustering and proposes a novel optimization framework DMO, ...

In this paper, we will examine the problem of clustering massive graph streams. Graph clustering poses significant challenges be- cause of the complex ...

In this paper, we have proposed an approach, Graph Stream. Classification with Side information (GSCS), which incorporates side information along with graph ...

Nov 13, 2015 · In this paper, we have proposed an approach, Graph Stream Classification with Side information (GSCS), which incorporates side information along with graph ...

Nov 21, 2024 · Many applications are generating side information associated with graph stream, such as terms and keywords in authorship graph of research ...

This paper proposes an approach, Graph Stream Classification with Side information (GSCS), which incorporates side information along with graph structure by ...

... side information to improve clustering performance, no matter which clustering algorithm is used. To this end, we propose a general boosting framework ...

Jul 1, 2016 · ABSTRACT. A graph stream refers to a continuous stream of edges, forming a huge and fast-evolving graph. The vast volume and high update.