This paper presents a recommendation algorithm that performs a query dependent random walk on a k-partite graph constructed from the various features relevant to the recommendatio...
Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William...
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
This paper presents a new framework for drawing graphs in three dimensions. In general, the new framework uses a divide and conquer approach. More specifically, the framework divi...
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Abstract. Graph mining approaches are extremely popular and effective in molecular databases. The vast majority of these approaches first derive interesting, i.e. frequent, patte...