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» Introduction to Data Mining and Knowledge Discovery
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KDD
2002
ACM
146views Data Mining» more  KDD 2002»
14 years 7 months ago
Closed Set Mining of Biological Data
We present a closed set data mining paradigm which is particularly e ective for uncovering the kind of deterministic, causal dependencies that characterize much of basic science. ...
John L. Pfaltz, Christopher M. Taylor
SIGKDD
2008
149views more  SIGKDD 2008»
13 years 7 months ago
Knowledge discovery from sensor data (SensorKDD)
Wide-area sensor infrastructures, remote sensors, RFIDs, and wireless sensor networks yield massive volumes of disparate, dynamic, and geographically distributed data. As such sen...
Ranga Raju Vatsavai, Olufemi A. Omitaomu, Joao Gam...
KDD
1998
ACM
140views Data Mining» more  KDD 1998»
13 years 11 months ago
Active Templates: Comprehensive Support for the Knowledge Discovery Process
The goal of Active Template research is to create a single, unified environment that a data analyst can use to carry out a knowledge discovery project, and to deliver the resultin...
Randy Kerber, Hal Beck, Tej Anand, Bill Smart
KDD
1995
ACM
95views Data Mining» more  KDD 1995»
13 years 11 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
EUSFLAT
2009
163views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
A Fuzzy Set Approach to Ecological Knowledge Discovery
Besides the problem of searching for effective methods for extracting knowledge from large databases (KDD) there are some additional problems with handling ecological data, namely ...
Arkadiusz Salski