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» Using and Learning Semantics in Frequent Subgraph Mining
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KDD
2012
ACM
242views Data Mining» more  KDD 2012»
13 years 2 months ago
Query-driven discovery of semantically similar substructures in heterogeneous networks
Heterogeneous information networks that contain multiple types of objects and links are ubiquitous in the real world, such as bibliographic networks, cyber-physical networks, and ...
Xiao Yu, Yizhou Sun, Peixiang Zhao, Jiawei Han
CIKM
2010
Springer
14 years 10 months ago
Mining interesting link formation rules in social networks
Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules...
Cane Wing-ki Leung, Ee-Peng Lim, David Lo, Jianshu...
103
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ICDM
2002
IEEE
109views Data Mining» more  ICDM 2002»
15 years 4 months ago
Using Text Mining to Infer Semantic Attributes for Retail Data Mining
Current Data Mining techniques usually do not have a mechanism to automatically infer semantic features inherent in the data being “mined”. The semantics are either injected i...
Rayid Ghani, Andrew E. Fano
HIS
2004
15 years 1 months ago
Hybrid Learning Scheme for Data Mining Applications
Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directl...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
DCC
2008
IEEE
15 years 11 months ago
An Approach to Graph and Netlist Compression
We introduce an EDIF netlist graph algorithm which is lossy with respect to the original byte stream but lossless in terms of the circuit information it contains based on a graph ...
Jeehong Yang, Serap A. Savari, Oskar Mencer