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Rule based systems for big data: a machine learning approach
The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evalu...
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
Springer
2016
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-23696-4 http://cds.cern.ch/record/2112839 |
_version_ | 1780948964860755968 |
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author | Liu, Han Gegov, Alexander Cocea, Mihaela |
author_facet | Liu, Han Gegov, Alexander Cocea, Mihaela |
author_sort | Liu, Han |
collection | CERN |
description | The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems. |
id | cern-2112839 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2016 |
publisher | Springer |
record_format | invenio |
spelling | cern-21128392021-04-21T20:00:56Zdoi:10.1007/978-3-319-23696-4http://cds.cern.ch/record/2112839engLiu, HanGegov, AlexanderCocea, MihaelaRule based systems for big data: a machine learning approachEngineeringThe ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.Springeroai:cds.cern.ch:21128392016 |
spellingShingle | Engineering Liu, Han Gegov, Alexander Cocea, Mihaela Rule based systems for big data: a machine learning approach |
title | Rule based systems for big data: a machine learning approach |
title_full | Rule based systems for big data: a machine learning approach |
title_fullStr | Rule based systems for big data: a machine learning approach |
title_full_unstemmed | Rule based systems for big data: a machine learning approach |
title_short | Rule based systems for big data: a machine learning approach |
title_sort | rule based systems for big data: a machine learning approach |
topic | Engineering |
url | https://dx.doi.org/10.1007/978-3-319-23696-4 http://cds.cern.ch/record/2112839 |
work_keys_str_mv | AT liuhan rulebasedsystemsforbigdataamachinelearningapproach AT gegovalexander rulebasedsystemsforbigdataamachinelearningapproach AT coceamihaela rulebasedsystemsforbigdataamachinelearningapproach |