We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Mining frequent structural patterns from graph databases is an interesting problem with broad applications. Most of the previous studies focus on pruning unfruitful search subspac...
Chen Wang, Wei Wang 0009, Jian Pei, Yongtai Zhu, B...
Given a quarter of petabyte click log data, how can we estimate the relevance of each URL for a given query? In this paper, we propose the Bayesian Browsing Model (BBM), a new mod...
While many clever techniques have been proposed for visual analysis, most of these are “one of” and it is not easy to see how to combine multiple techniques. We propose an alg...
Anna A. Shaverdian, Hao Zhou, George Michailidis, ...
Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applicatio...
Yan Xing, Michael G. Madden, Jim Duggan, Gerard Ly...