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RSCTC
1998
Springer
175views Fuzzy Logic» more  RSCTC 1998»
14 years 2 months ago
Business Process Understanding: Mining Many Datasets
Abstract. Institutional databases can be instrumental in understanding a business process, but additional data may broaden the empirical perspective on the investigated process. We...
Jan M. Zytkow, Arun P. Sanjeev
EWSN
2008
Springer
14 years 9 months ago
Discovery of Frequent Distributed Event Patterns in Sensor Networks
Today it is possible to deploy sensor networks in the real world and collect large amounts of raw sensory data. However, it remains a major challenge to make sense of sensor data, ...
Kay Römer
GCB
2000
Springer
99views Biometrics» more  GCB 2000»
14 years 1 months ago
Structure Motif Discovery and Mining the PDB
We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the prote...
Inge Jonassen, Ingvar Eidhammer, Darrell Conklin, ...
EUSFLAT
2007
105views Fuzzy Logic» more  EUSFLAT 2007»
13 years 11 months ago
SPoID: Do Not Throw Meaningful Incomplete Sequences Away!
Industrial databases often contain a large amount of unfilled information. During the knowledge discovery process one processing step is often necessary in order to remove these ...
Céline Fiot, Anne Laurent, Maguelonne Teiss...
CINQ
2004
Springer
125views Database» more  CINQ 2004»
14 years 3 months ago
The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery
Many researchers in our community (this author included) regularly emphasize the role constraints play in improving performance of data-mining algorithms. This emphasis has led to ...
Roberto J. Bayardo