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» Using Anonymized Data for Classification
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IJON
2008
173views more  IJON 2008»
15 years 16 days ago
Support vector machine classification for large data sets via minimum enclosing ball clustering
Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitabl...
Jair Cervantes, Xiaoou Li, Wen Yu, Kang Li
IASSE
2004
15 years 1 months ago
A Model for Multi-relational Data Mining on Demand Forecasting
Accurate demand forecasting remains difficult and challenging in today's competitive and dynamic business environment, but even a little improvement in demand prediction may ...
Qin Ding, Bhavin Parikh
90
Voted
TDP
2008
111views more  TDP 2008»
15 years 13 days ago
Statistical Disclosure Control for Microdata Using the R-Package sdcMicro
The demand for high quality microdata for analytical purposes has grown rapidly among researchers and the public over the last few years. In order to respect existing laws on data ...
Matthias Templ
PERCOM
2008
ACM
16 years 4 days ago
Composition and Generalization of Context Data for Privacy Preservation
This paper presents preliminary results on anonymization and obfuscation techniques to preserve users' privacy in context-aware service provisioning. The techniques are based...
Linda Pareschi, Daniele Riboni, Alessandra Agostin...
76
Voted
INTERSPEECH
2010
14 years 7 months ago
Identifying articulatory goals from kinematic data using principal differential analysis
Articulatory goals can be highly indicative of lexical intentions, but are rarely used in speech classification tasks. In this paper we show that principal differential analysis c...
Michael Reimer, Frank Rudzicz