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Titlebook: Data Warehousing and Knowledge Discovery; 13th International C Alfredo Cuzzocrea,Umeshwar Dayal Conference proceedings 2011 Springer-Verlag

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發(fā)表于 2025-3-23 12:40:54 | 只看該作者
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發(fā)表于 2025-3-24 04:33:02 | 只看該作者
Vertical Fragmentation of XML Data Warehouses Using Frequent Path Setsk has been done on XML warehouses. In this paper, we address the problem of vertical fragmentation of XML Warehouses. We use Association Rules to partition and cluster frequent path sets into fragments. In addition, at the schema level, we address and solve the problem of reconstructing the original
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發(fā)表于 2025-3-24 09:48:33 | 只看該作者
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發(fā)表于 2025-3-24 16:54:00 | 只看該作者
Tagged MapReduce: Efficiently Computing Multi-analytics Using MapReducess creates (key, value) pairs, while the reduce phase aggregates same-key values. In other words, a MapReduce application defines and reduces one set of values for each key, which means that the user only knows .. of the .. Advanced OLAP applications however, require multiple sets to be defined and
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發(fā)表于 2025-3-24 21:43:16 | 只看該作者
Frequent Pattern Mining from Time-Fading Streams of Uncertain Datao the inherited limitation of the sensors, data in these streams can be uncertain. To discover useful knowledge in the form of frequent patterns from streams of uncertain data, a few algorithms have been developed. They mostly use the sliding window model for processing and mining data streams. Howe
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發(fā)表于 2025-3-25 02:09:28 | 只看該作者
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