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SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
14 years 6 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
GG
2004
Springer
14 years 2 months ago
Analysis of Metabolic Pathways by Graph Transformation
Biochemical pathways, such as metabolic, regulatory, and signal transduction pathways, constitute complex networks of functional and physical interactions between molecular species...
Francesc Rosselló, Gabriel Valiente
PCM
2004
Springer
107views Multimedia» more  PCM 2004»
14 years 2 months ago
Complete Performance Graphs in Probabilistic Information Retrieval
The performance of a Content-Based Image Retrieval (CBIR) system presented in the form of Precision-Recall or PrecisionScope graphs offers an incomplete overview of the system und...
Nicu Sebe, Dionysius P. Huijsmans, Qi Tian, Theo G...
PAKDD
2010
ACM
169views Data Mining» more  PAKDD 2010»
14 years 2 months ago
oddball: Spotting Anomalies in Weighted Graphs
Given a large, weighted graph, how can we find anomalies? Which rules should be violated, before we label a node as an anomaly? We propose the OddBall algorithm, to find such nod...
Leman Akoglu, Mary McGlohon, Christos Faloutsos
CORR
2011
Springer
199views Education» more  CORR 2011»
13 years 4 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...