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» Discovering Classification from Data of Multiple Sources
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IEAAIE
2005
Springer
14 years 1 months ago
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization
Association rules discovery is a fundamental task in spatial data mining where data are naturally described at multiple levels of granularity. ARES is a spatial data mining system ...
Annalisa Appice, Paolo Buono
BMCBI
2006
190views more  BMCBI 2006»
13 years 7 months ago
VANTED: A system for advanced data analysis and visualization in the context of biological networks
Background: Recent advances with high-throughput methods in life-science research have increased the need for automatized data analysis and visual exploration techniques. Sophisti...
Björn H. Junker, Christian Klukas, Falk Schre...
TCBB
2010
80views more  TCBB 2010»
13 years 6 months ago
On the Importance of Comprehensible Classification Models for Protein Function Prediction
—The literature on protein function prediction is currently dominated by works aimed at maximizing predictive accuracy, ignoring the important issues of validation and interpreta...
Alex Alves Freitas, Daniela Wieser, Rolf Apweiler
SIGMOD
2008
ACM
136views Database» more  SIGMOD 2008»
14 years 7 months ago
Mining relationships among interval-based events for classification
Existing temporal pattern mining assumes that events do not have any duration. However, events in many real world applications have durations, and the relationships among these ev...
Dhaval Patel, Wynne Hsu, Mong-Li Lee
DAWAK
2008
Springer
13 years 9 months ago
Mining Serial Episode Rules with Time Lags over Multiple Data Streams
The problem of discovering episode rules from static databases has been studied for years due to its wide applications in prediction. In this paper, we make the first attempt to st...
Tung-Ying Lee, En Tzu Wang, Arbee L. P. Chen