We focus on large graphs where nodes have attributes, such as a social network where the nodes are labelled with each person's job title. In such a setting, we want to find s...
Hanghang Tong, Christos Faloutsos, Brian Gallagher...
Documents, such as those seen on Wikipedia and Folksonomy, have tended to be assigned with multiple topics as a meta-data. Therefore, it is more and more important to analyze a re...
The importance of dominance and skyline analysis has been well recognized in multi-criteria decision making applications. Most previous studies assume a fixed order on the attribu...
Raymond Chi-Wing Wong, Jian Pei, Ada Wai-Chee Fu, ...
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...