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KDD
2009
ACM
163views Data Mining» more  KDD 2009»
16 years 13 days ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
16 years 13 days ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
MOBIHOC
2009
ACM
16 years 13 days ago
Spectrum auction framework for access allocation in cognitive radio networks
Cognitive radio networks are emerging as a promising technology for the efficient use of radio spectrum. In these networks, there are two categories of networks on different chann...
Gaurav S. Kasbekar, Saswati Sarkar
KDD
2008
ACM
232views Data Mining» more  KDD 2008»
16 years 9 days ago
Anticipating annotations and emerging trends in biomedical literature
The BioJournalMonitor is a decision support system for the analysis of trends and topics in the biomedical literature. Its main goal is to identify potential diagnostic and therap...
Bernd Wachmann, Dmitriy Fradkin, Fabian Mörch...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 9 days ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson