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KDD
2009
ACM
132views Data Mining» more  KDD 2009»
14 years 8 months ago
Learning patterns in the dynamics of biological networks
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
IJMMS
2007
166views more  IJMMS 2007»
13 years 7 months ago
Visualization of large networks with min-cut plots, A-plots and R-MAT
What does a ‘normal’ computer (or social) network look like? How can we spot ‘abnormal’ sub-networks in the Internet, or web graph? The answer to such questions is vital f...
Deepayan Chakrabarti, Christos Faloutsos, Yiping Z...
ICCS
2007
Springer
14 years 1 months ago
Learning Common Outcomes of Communicative Actions Represented by Labeled Graphs
We build a generic methodology based on learning and reasoning to detect specific attitudes of human agents and patterns of their interactions. Human attitudes are determined in te...
Boris Galitsky, Boris Kovalerchuk, Sergei O. Kuzne...
IS
2010
13 years 6 months ago
Tree pattern mining with tree automata constraints
Most work on pattern mining focuses on simple data structures such as itemsets and sequences of itemsets. However, a lot of recent applications dealing with complex data like chem...
Sandra de Amo, Nyara A. Silva, Ronaldo P. Silva, F...
SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
14 years 7 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...