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Using feature construction for dimensionality reduction in big data scenarios to allow real time classification of sequence data

  • A sequence of transactions represents a complex and multi dimensional type of data. Feature construction can be used to reduce the data´s dimensionality to find behavioural patterns within such sequences. The patterns can be expressed using the blue prints of the constructed relevant features. These blue prints can then be used for real time classification on other sequences.

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Author of HS ReutlingenLaux, Friedrich
Erschienen in:Digital enterprise computing (DEC 2015)
Publisher:Gesellschaft für Informatik
Place of publication:Bonn
Editor:Alfred ZimmermannORCiD, Alexander RossmannORCiD
Document Type:Conference proceeding
Publication year:2015
Tag:big data; feature construction; real time classification
Page Number:11
First Page:259
Last Page:269
PPN:Im Katalog der Hochschule Reutlingen ansehen
DDC classes:004 Informatik
Open access?:Ja
Licence (German):License Logo  Open Access