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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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21#
發(fā)表于 2025-3-25 07:03:04 | 只看該作者
Top_Keyword: An Aggregation Function for Textual Document OLAPional databases as well as an adapted framework for their analysis. This paper presents a new aggregation function that aggregates textual data in an OLAP environment. The . function (. for short) represents a set of documents by their most significant terms using a weighing function from information retrieval: ....
22#
發(fā)表于 2025-3-25 08:16:55 | 只看該作者
Jag Free Images on a Raster CRTrver. In this paper, we propose a generic tool for summarizing distributed data streams where the amount of data being collected from each sensor adapts to data characteristics. Experiments done on electric power consumption real data are reported and show the efficiency of the proposed approach.
23#
發(fā)表于 2025-3-25 12:59:05 | 只看該作者
24#
發(fā)表于 2025-3-25 16:48:52 | 只看該作者
25#
發(fā)表于 2025-3-25 21:14:13 | 只看該作者
Computer Games as a Sociocultural Phenomenoned on the use of activity diagrams enriched with object flows, aimed at expressing functional, dynamic, and static aspects in an integrated fashion. The paper is completed by examples taken from a real case study in the commercial area.
26#
發(fā)表于 2025-3-26 00:22:20 | 只看該作者
https://doi.org/10.1057/9780230583306in this paper, we describe how to obtain the data-cube metadata for “.n-.ine .nalytical .rocessing” (OLAP) tools. As a proof of concept, our approach has been implemented in the . development platform, thus showing its feasibility.
27#
發(fā)表于 2025-3-26 08:08:18 | 只看該作者
28#
發(fā)表于 2025-3-26 08:43:27 | 只看該作者
29#
發(fā)表于 2025-3-26 13:02:40 | 只看該作者
30#
發(fā)表于 2025-3-26 19:09:29 | 只看該作者
Kikuo Fujimura,Tosiyasu L. Kuniiue is compared with the one of the method ., the state-of-the-art privacy preserving OLAP perturbation-based technique, under several perspectives of analysis. The derived experimental results confirm to us the benefits deriving from adopting our proposed framework for the goal of preserving the privacy of OLAP data cubes.
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