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» Process Knowledge and Data Quality Outcomes
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CCE
2008
13 years 7 months ago
A hierarchical decision procedure for productivity innovation in large-scale petrochemical processes
Maintaining the best quality is essential for the survival of a company in a globally competitive world. Six Sigma activity has been widely accepted as one of the most efficient a...
Chonghun Han, Minjin Kim, En Sup Yoon
TSE
1998
83views more  TSE 1998»
13 years 6 months ago
Cost-Effective Analysis of In-Place Software Processes
—Process studies and improvement efforts typically call for new instrumentation on the process in order to collect the data they have deemed necessary. This can be intrusive and ...
Jonathan E. Cook, Lawrence G. Votta, Alexander L. ...
BIS
2009
168views Business» more  BIS 2009»
13 years 8 months ago
Defining Adaptation Constraints for Business Process Variants
Abstract. In current dynamic business environment, it has been argued that certain characteristics of ad-hocism in business processes are desirable. Such business processes typical...
Ruopeng Lu, Shazia Wasim Sadiq, Guido Governatori,...
CEC
2007
IEEE
13 years 11 months ago
Evolution of classification rules for comprehensible knowledge discovery
This article, which lies within the data mining framework, proposes a method to build classifiers based on the evolution of rules. The method, named REC (Rule Evolution for Classif...
Emiliano Carreno, Guillermo Leguizamón, Nea...
HIS
2004
13 years 8 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...