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Titlebook: Data Warehousing and Knowledge Discovery; 7th International Co A Min Tjoa,Juan Trujillo Conference proceedings 2005 Springer-Verlag Berlin

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书目名称Data Warehousing and Knowledge Discovery
副标题7th International Co
编辑A Min Tjoa,Juan Trujillo
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Warehousing and Knowledge Discovery; 7th International Co A Min Tjoa,Juan Trujillo Conference proceedings 2005 Springer-Verlag Berlin
描述For more than a decade, data warehousing and knowledge discovery technologies have been developing into key technologies for decision-making processes in com- nies. Since 1999, due to the relevant role of these technologies in academia and ind- try, the Data Warehousing and Knowledge Discovery (DaWaK) conference series have become an international forum where both practitioners and researchers share their findings, publish their relevant results and dispute in depth research issues and experiences on data warehousing and knowledge discovery systems and applications. The 7th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2005) continued series of successful conferences dedicated to these topics. In this edition, the conference tried to provide the right, logical balance between data warehousing and knowledge discovery. Regarding data warehousing, papers cover different relevant and still unsolved research problems, such as the modelling of ETL processes and integration problems, designing OLAP technologies from XML do- ments, modelling data warehouses and data mining applications together, impro- ments in query processing, partitioning and implementation
出版日期Conference proceedings 2005
关键词algorithms; classification; data mining; data warehouse; database; knowledge discovery; service-oriented c
版次1
doihttps://doi.org/10.1007/11546849
isbn_softcover978-3-540-28558-8
isbn_ebook978-3-540-31732-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2005
The information of publication is updating

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Progressive Ranking of Range Aggregateshms is based on both ranking and cumulative information to progressively rank aggregation results. Furthermore we empirically evaluate our techniques and the experimental results show that the query cost is improved significantly.
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Ronen Barzel,John R. Hughes,Daniel N. Woodhms is based on both ranking and cumulative information to progressively rank aggregation results. Furthermore we empirically evaluate our techniques and the experimental results show that the query cost is improved significantly.
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Conference proceedings 2005different relevant and still unsolved research problems, such as the modelling of ETL processes and integration problems, designing OLAP technologies from XML do- ments, modelling data warehouses and data mining applications together, impro- ments in query processing, partitioning and implementation
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Graph-Based Modeling of ETL Activities with Multi-level Transformations and Updates(c) transforming the graph to allow zoom-in/out at multiple levels of abstraction (i.e., passing from the detailed description of the graph at the attribute level to more compact variants involving programs, relations and queries and vice-versa).
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On Efficient Storing and Processing of Long Aggregate Lists. We present test results and we use them for estimating the best combination of the configuration parameters: number of pages, size of a single page and number of available database connections. The Materialized Aggregate List can be applied on every aggregation level in various indexing structures, such as, an aR-tree.
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