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» Discovering Case Knowledge Using Data Mining
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GI
1998
Springer
14 years 2 months ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller
APCCM
2006
13 years 11 months ago
Network data mining: methods and techniques for discovering deep linkage between attributes
Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of `emergent' patterns and tre...
John Galloway, Simeon J. Simoff
KDD
1997
ACM
120views Data Mining» more  KDD 1997»
14 years 2 months ago
Discovering Trends in Text Databases
We describe a system we developed for identifying trends in text documents collected over a period of time. Trends can be used, for example, to discover that a company is shifting...
Brian Lent, Rakesh Agrawal, Ramakrishnan Srikant
ICDE
2006
IEEE
152views Database» more  ICDE 2006»
14 years 11 months ago
Mining Actionable Patterns by Role Models
Data mining promises to discover valid and potentially useful patterns in data. Often, discovered patterns are not useful to the user. "Actionability" addresses this pro...
Ke Wang, Yuelong Jiang, Alexander Tuzhilin
KDD
1995
ACM
95views Data Mining» more  KDD 1995»
14 years 1 months ago
On Subjective Measures of Interestingness in Knowledge Discovery
One of the central problems in the field of knowledge discovery is the development of good measures of interestingness of discovered patterns. Such measures of interestingness are...
Abraham Silberschatz, Alexander Tuzhilin