Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...
This paper studies how to incorporate side information (such as users’ feedback) in measuring node proximity on large graphs. Our method (ProSIN) is motivated by the well-studie...
We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and ...
Duen Horng Chau, Christos Faloutsos, Hanghang Tong...
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...