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Data Preparation in the MineCor KDD Framework

Authors:
Christian Ernst
Alain Casali

Keywords: Data Mining, Semiconductor Manufacturing, De- cision Correlation Rule, Data Preparation.

Abstract:
Yield enhancement is a key issue in semiconductor manufacturing. Data mining tools can therefore be helpful, by extracting hidden links between numerous complex pro- cess control parameters. In order to highlight correlations between such parameters, we developed a complete Knowledge Discovery in Databases (KDD) model, called MineCor. Its mining heart uses a new method derived from association rules programming, based on lectic search and contingency vectors. After recalling these concepts, this paper focuses on data preprocessing and transformation functions, which have an important impact on final results. An overall presentation of these functions, of some significant experimental results and of associated performances are provided and finally discussed.

Pages: 16 to 22

Copyright: Copyright (c) IARIA, 2011

Publication date: October 23, 2011

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-162-5

Location: Barcelona, Spain

Dates: from October 23, 2011 to October 29, 2011