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Titlebook: Web Information Systems Engineering – WISE 2014 Workshops; 15th International W Boualem Benatallah,Azer Bestavros,Yanchun Zhang Conference

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樓主: Osteopenia
61#
發(fā)表于 2025-4-1 02:48:45 | 只看該作者
Xiaofeng Du,William Songtate’) entered the political lexicon. The first section of this chapter examines how state failure became a core concern of international politics, with profound consequences for foreign, security and defence, and development policy. What made the 1990s receptive to this ‘new’ concept? The second se
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發(fā)表于 2025-4-1 09:06:38 | 只看該作者
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發(fā)表于 2025-4-1 10:40:01 | 只看該作者
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發(fā)表于 2025-4-1 18:39:10 | 只看該作者
Web Information Systems Engineering – WISE 2014 Workshops978-3-319-20370-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
66#
發(fā)表于 2025-4-1 23:04:55 | 只看該作者
Boualem Benatallah,Azer Bestavros,Yanchun ZhangIncludes supplementary material:
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發(fā)表于 2025-4-2 06:21:19 | 只看該作者
68#
發(fā)表于 2025-4-2 07:15:33 | 只看該作者
Quality Improvement Framework for Business Oriented Geo-spatial Data,data analytic result from geo-spatial related data, low quality data means wrong or inappropriate decisions, which could have substantial effects on a business’s future. In this paper, we propose a framework that can systematically ensure and improve geo-spatial data quality throughout the whole life cycle of data.
69#
發(fā)表于 2025-4-2 14:28:58 | 只看該作者
Data Streams Quality Evaluation for the Generation of Alarms in Health Domain,focuses on processing the sensors data streams taking into account data quality. In order to achieve this, a data quality model for this kind of data streams and an architecture for the monitoring system are proposed. Besides, our work induces a mechanism for avoiding false alarms generated by data quality problems.
70#
發(fā)表于 2025-4-2 17:07:39 | 只看該作者
Quality Improvement Framework for Business Oriented Geo-spatial Data,data analytic result from geo-spatial related data, low quality data means wrong or inappropriate decisions, which could have substantial effects on a business’s future. In this paper, we propose a framework that can systematically ensure and improve geo-spatial data quality throughout the whole life cycle of data.
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