Advances in Knowledge Discovery and Management
Fabrice Guillet · Bruno Pinaud · Gilles Venturini · Djamel Abdelkader Zighed
dek 2012 · Studies in Computational Intelligence Kitab 471 · Springer
E-kitab
222
Səhifələr
reportReytinqlər və rəylər doğrulanmır Ətraflı Məlumat
Bu e-kitab haqqında
The recent and novel research contributions collected in this book are extended and
reworked versions of a selection of the best papers that were originally presented in
French at the EGC’2011 Conference held in Brest, France, on January 2011.
EGC stands for "Extraction et Gestion des connaissances" in French, and means "Knowledge Discovery and Management" or KDM.
KDM is concerned with the works in computer science at the interface between data and knowledge; such as Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web.
This book is intended to be read by all researchers interested in these fields, including
PhD or MSc students, and researchers from public or private laboratories. It
concerns both theoretical and practical aspects of KDM.
This book has been structured in two parts.
The first part, entitled “Data Mining, classification and queries”, deals with rule and pattern mining, with topological approaches
and with OLAP.
The second part of the book, entitled “Ontology and Semantic”, is related
to knowledge-based and user-centered approaches in KDM.
reworked versions of a selection of the best papers that were originally presented in
French at the EGC’2011 Conference held in Brest, France, on January 2011.
EGC stands for "Extraction et Gestion des connaissances" in French, and means "Knowledge Discovery and Management" or KDM.
KDM is concerned with the works in computer science at the interface between data and knowledge; such as Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web.
This book is intended to be read by all researchers interested in these fields, including
PhD or MSc students, and researchers from public or private laboratories. It
concerns both theoretical and practical aspects of KDM.
This book has been structured in two parts.
The first part, entitled “Data Mining, classification and queries”, deals with rule and pattern mining, with topological approaches
and with OLAP.
The second part of the book, entitled “Ontology and Semantic”, is related
to knowledge-based and user-centered approaches in KDM.
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