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» Using a Hash-Based Method for Apriori-Based Graph Mining
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PKDD
2010
Springer
155views Data Mining» more  PKDD 2010»
13 years 7 months ago
Latent Structure Pattern Mining
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
13 years 10 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Erion Plaku, Lydia E. Kavraki
CIKM
2009
Springer
14 years 3 months ago
Graph classification based on pattern co-occurrence
Subgraph patterns are widely used in graph classification, but their effectiveness is often hampered by large number of patterns or lack of discrimination power among individual p...
Ning Jin, Calvin Young, Wei Wang
PKDD
2000
Springer
151views Data Mining» more  PKDD 2000»
14 years 4 days ago
Discovery of Characteristic subgraph Patterns Using Relative Indexing and the Cascade Model
: Relational representation of objects using graphs reveals much information that cannot be obtained by attribute value representations alone. There are already many databases that...
Takashi Okada, Mayumi Oyama
DATESO
2010
148views Database» more  DATESO 2010»
13 years 6 months ago
Using Spectral Clustering for Finding Students' Patterns of Behavior in Social Networks
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...
Gamila Obadi, Pavla Drázdilová, Jan ...