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Titlebook: Data Warehousing and Knowledge Discovery; 5th International Co Yahiko Kambayashi,Mukesh Mohania,Wolfram Wöß Conference proceedings 2003 Spr

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书目名称Data Warehousing and Knowledge Discovery
副标题5th International Co
编辑Yahiko Kambayashi,Mukesh Mohania,Wolfram Wöß
视频videohttp://file.papertrans.cn/264/263210/263210.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Warehousing and Knowledge Discovery; 5th International Co Yahiko Kambayashi,Mukesh Mohania,Wolfram Wöß Conference proceedings 2003 Spr
描述.This book constitutes the refereed proceedings of the 5th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2003, held in Prague, Czech Republic in September 2003....The 41 revised full papers presented were carefully reviewed and selected from more than 130 submissions. The papers are organized in topical sections on data cubes and queries, multidimensional data models, Web warehousing, change detection, Web mining and association rules, association rules and decision trees, clustering, association rule mining, data analysis and discovery, ontologies and improving data quality, queries and data patterns, improving database query engines, and sampling and vector classification..
出版日期Conference proceedings 2003
关键词Data Warehouse; classification; clustering; data analysis; database; database systems; performance; perform
版次1
doihttps://doi.org/10.1007/b11825
isbn_softcover978-3-540-40807-9
isbn_ebook978-3-540-45228-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2003
The information of publication is updating

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Computer Integrated Manufacturing K-means based classifiers. The experimental results show that IBC significantly outperforms the companion methods in execution efficiency for dataset with categorical attributes of sparse distribution while attaining approximately the same classification accuracies. Consequently, IBC is considered
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A Temporal Study of Data Sources to Load a Corporate Data Warehousetime or not, we could obtain the valid time for the data warehouse or not. The aim of this paper is to present a temporal study of the different kinds of data sources to load a corporate data warehouse, using a bitemporal storage structure.
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Performance Tests in Data Warehousing ETLM Process for Detection of Changes in Data Origin The technique is simple and can be applied to all four scenarios above. To prove the efficiency of our technique, in this article we do comparative performance tests between these approaches. We performed two benchmarks: the first one using synthetic data and the second one using the real data from
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