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Titlebook: Data Warehousing and Knowledge Discovery; 10th International C Il-Yeol Song,Johann Eder,Tho Manh Nguyen Conference proceedings 2008 Springe

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书目名称Data Warehousing and Knowledge Discovery
副标题10th International C
编辑Il-Yeol Song,Johann Eder,Tho Manh Nguyen
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Warehousing and Knowledge Discovery; 10th International C Il-Yeol Song,Johann Eder,Tho Manh Nguyen Conference proceedings 2008 Springe
描述Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations as a means of improving their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision making process, the data to be processed is becoming more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge disc- ery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area. During the past few years, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has become one of the most important international scientific events to bring together researchers, developers and practitioners. The DaWaK conferences serve as a prominent forum for discussing the latest research issues and experiences in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. This year’s conference, the 10th Int- national Conference on Data Warehousing and Knowledge Discovery (DaWaK 2008), continued the tradi
出版日期Conference proceedings 2008
关键词Clustering; classification; data mining; data warehouse; knowledge; knowledge discovery; learning; machine
版次1
doihttps://doi.org/10.1007/978-3-540-85836-2
isbn_softcover978-3-540-85835-5
isbn_ebook978-3-540-85836-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2008
The information of publication is updating

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Efficient Data Distribution for DWS DWS. The experimental results show that the effective loading of the nodes in a DWS system must consider complementary effects, minimizing the number of distinct keys of any large dimension in the fact tables in each node, as well as splitting correlated rows among the nodes.
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A Hierarchical Space Indexing MethodP methods in experiments based on two UCI datasets and two utility measures. Preliminary results show that our method can better protect against the distribution attack and provide good balance between privacy and data utility.
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