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Titlebook: Innovative Applications in Data Mining; Nadia Nedjah,Luiza Macedo Mourelle,Janusz Kacprzyk Book 2009 Springer-Verlag Berlin Heidelberg 200

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书目名称Innovative Applications in Data Mining
编辑Nadia Nedjah,Luiza Macedo Mourelle,Janusz Kacprzyk
视频videohttp://file.papertrans.cn/468/467313/467313.mp4
概述Recent advances in data mining
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Innovative Applications in Data Mining;  Nadia Nedjah,Luiza Macedo Mourelle,Janusz Kacprzyk Book 2009 Springer-Verlag Berlin Heidelberg 200
描述.Data mining consists of attempting to discover novel and useful knowledge from data, trying to find patterns among datasets that can help in intelligent decision making. However, reports of real-world case studies are not generally detailed in the literature, due to the fact that they are usually based on proprietary datasets, making it impossible to publish the results. This kind of situation makes hard to evaluate, in a precise way, the degree of effectiveness of data mining techniques in real-world applications. On the other hand, researchers of this field of expertise usually exploit public-domain datasets...This volume offers a wide spectrum of research work developed for data mining for real-world application. In the following, we give a brief introduction of the chapters that are included in this book..
出版日期Book 2009
关键词algorithm; classification; clustering; computational intelligence; data mining; intelligence; knowledge; li
版次1
doihttps://doi.org/10.1007/978-3-540-88045-5
isbn_softcover978-3-642-09976-2
isbn_ebook978-3-540-88045-5Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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Clustering Dynamic Web Usage Data,tionary approach based on an intelligent clustering approach. We carry out various clustering strategies that are applied on time sub-periods. To validate our approach we apply two external evaluation criteria which compare different partitions from the same data set. Our experiments show that the p
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1860-949X among datasets that can help in intelligent decision making. However, reports of real-world case studies are not generally detailed in the literature, due to the fact that they are usually based on proprietary datasets, making it impossible to publish the results. This kind of situation makes hard t
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