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Realtime data mining: self-learning techniques for recommendation engines

Detalles Bibliográficos
Autores principales: Paprotny, Alexander, Thess, Michael
Lenguaje:eng
Publicado: Springer 2013
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-01321-3
http://cds.cern.ch/record/1642218
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author Paprotny, Alexander
Thess, Michael
author_facet Paprotny, Alexander
Thess, Michael
author_sort Paprotny, Alexander
collection CERN
id cern-1642218
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2013
publisher Springer
record_format invenio
spelling cern-16422182021-04-21T21:22:58Zdoi:10.1007/978-3-319-01321-3http://cds.cern.ch/record/1642218engPaprotny, AlexanderThess, MichaelRealtime data mining: self-learning techniques for recommendation enginesMathematical Physics and MathematicsSpringeroai:cds.cern.ch:16422182013
spellingShingle Mathematical Physics and Mathematics
Paprotny, Alexander
Thess, Michael
Realtime data mining: self-learning techniques for recommendation engines
title Realtime data mining: self-learning techniques for recommendation engines
title_full Realtime data mining: self-learning techniques for recommendation engines
title_fullStr Realtime data mining: self-learning techniques for recommendation engines
title_full_unstemmed Realtime data mining: self-learning techniques for recommendation engines
title_short Realtime data mining: self-learning techniques for recommendation engines
title_sort realtime data mining: self-learning techniques for recommendation engines
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-01321-3
http://cds.cern.ch/record/1642218
work_keys_str_mv AT paprotnyalexander realtimedataminingselflearningtechniquesforrecommendationengines
AT thessmichael realtimedataminingselflearningtechniquesforrecommendationengines