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ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
15 years 3 months ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
NAACL
2007
14 years 11 months ago
OMS-J: An Opinion Mining System for Japanese Weblog Reviews Using a Combination of Supervised and Unsupervised Approaches
We introduce a simple opinion mining system for analyzing Japanese Weblog reviews called OMS-J. OMS-J is designed to provide an intuitive visual GUI of opinion mining graphs for a...
Guangwei Wang, Kenji Araki
SIGKDD
2008
125views more  SIGKDD 2008»
14 years 9 months ago
Incremental pattern discovery on streams, graphs and tensors
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
Jimeng Sun
SDM
2011
SIAM
269views Data Mining» more  SDM 2011»
14 years 8 days ago
Semi-Supervised Convolution Graph Kernels for Relation Extraction
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
Xia Ning, Yanjun Qi
GBRPR
2009
Springer
15 years 4 months ago
Graph Matching Based on Node Signatures
We present an algorithm for graph matching in a pattern recognition context. This algorithm deals with weighted graphs, based on new structural and topological node signatures. Usi...
Salim Jouili, Salvatore Tabbone