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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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Answering Joint Queries from Multiple Aggregate OLAP Databases is more expensive computationally than P. Our contribution is in proposing a third new method, called the “Partial-Pre-aggregation” method (PP), which is significantly less expensive than F, but is just as accurate.
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CPM: A Cube Presentation Model for OLAP novel presentational model for OLAP screens, intuitively based on the geometrical representation of a cube and its human perception in the space. Moreover, we show how the logical and the presentational models are integrated smoothly. Finally, we describe how typical OLAP operations can be easily mapped to the CPM.
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An Approach to Enabling Spatial OLAP by Aggregating on Spatial Hierarchyaterialization, which in turn are leveraged by the OLAP system to efficiently answer spatial OLAP queries. Our prototype system shows that the proposed approach could be integrated easily into the existing data warehouse and OLAP systems to support spatial analysis. Preliminary experiment results are also presented.
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A Multidimensional Aggregation Object (MAO) Framework for Computing Distributive Aggregationshow that caching intermediate aggregated data can significantly improve performance. Incremental compensating and full recomputing cache-updating approaches are proposed. Execution plans for deriving the aggregations from MAOs are presented. The proposed data aggregation technique can be applied to data-warehousing, OLAP, and data mining tasks.
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MetaCube XTM: A Multidimensional Metadata Approach for Semantic Web Warehousing Systemserogeneous is presented. As a result, the interoperability is accomplished by a schema integration approach based on XTM. Furthermore, important implementation aspects of the MetaCube-XTM prototype, which makes use of the Meta Data Interchange Specification (MDIS), and the Open Information Model, complete the presentation of our approach.
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Conference proceedings 2003 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..
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/263210.jpg
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