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ICDM
2007
IEEE
136views Data Mining» more  ICDM 2007»
16 years 1 months ago
Recommendation via Query Centered Random Walk on K-Partite Graph
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...
IJCNN
2006
IEEE
16 years 1 months ago
A Comparison between Recursive Neural Networks and Graph Neural Networks
— 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...
GD
2005
Springer
16 years 1 months ago
MultiPlane: A New Framework for Drawing Graphs in Three Dimensions
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...
Seok-Hee Hong
COLT
2004
Springer
16 years 1 months ago
Regularization and Semi-supervised Learning on Large Graphs
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...
Mikhail Belkin, Irina Matveeva, Partha Niyogi
DIS
2004
Springer
16 years 1 months ago
Predictive Graph Mining
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...
Andreas Karwath, Luc De Raedt