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KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 9 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
SIGKDD
2010
126views more  SIGKDD 2010»
13 years 3 months ago
MultiClust 2010: discovering, summarizing and using multiple clusterings
Traditional clustering focuses on finding a single best clustering solution from data. However, given a single data set, one could interpret it in different ways. This is particul...
Xiaoli Z. Fern, Ian Davidson, Jennifer G. Dy
ICDM
2007
IEEE
192views Data Mining» more  ICDM 2007»
14 years 3 months ago
Discovering Temporal Communities from Social Network Documents
Discovering communities from documents involved in social discourse is an important topic in social network analysis, enabling greater understanding of the relationships among act...
Ding Zhou, Isaac G. Councill, Hongyuan Zha, C. Lee...
AMINING
2003
Springer
261views Data Mining» more  AMINING 2003»
14 years 1 months ago
Micro View and Macro View Approaches to Discovered Rule Filtering
A data mining system can semi-automatically discover knowledge by mining a large volume of data, but the discovered knowledge is not always novel and may contain unreasonable facts...
Yasuhiko Kitamura, Akira Iida, Keunsik Park
KDD
1998
ACM
118views Data Mining» more  KDD 1998»
14 years 28 days ago
A Belief-Driven Method for Discovering Unexpected Patterns
Several pattern discovery methods proposed in the data mining literature have the drawbacks that they discover too many obvious or irrelevant patterns and that they do not leverag...
Balaji Padmanabhan, Alexander Tuzhilin