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Titlebook: Scientific and Statistical Database Management; 24th International C Anastasia Ailamaki,Shawn Bowers Conference proceedings 2012 Springer-V

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發(fā)表于 2025-3-28 18:22:51 | 只看該作者
Navigating Oceans of Dataoaches CMOP has followed to help operational, science and resource managers locate, view and analyze data, including the Data Explorer, Data Near Here, and topical “watch pages.” From these examples, and user experiences with them, we draw lessons about supporting users of collaborative “science obs
42#
發(fā)表于 2025-3-28 21:23:38 | 只看該作者
Probabilistic Range Monitoring of Streaming Uncertain Positions in GeoSocial Networksidates. Approximate answers are reported with confidence margins, as a means of providing quality guarantees and suppressing useless messages. We complement our analysis with a comprehensive experimental study, which indicates that the proposed technique offers almost real-time notification with tol
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發(fā)表于 2025-3-29 02:10:44 | 只看該作者
44#
發(fā)表于 2025-3-29 03:42:42 | 只看該作者
45#
發(fā)表于 2025-3-29 08:08:55 | 只看該作者
Partitioning and Multi-core Parallelization of Multi-equation Forecast Modelsary values and improve the utilization of the CPU cache. Furthermore, we utilize the capabilities of modern multi-core hardware and parallelize the model estimation. Our experimental results on real-world data show speedups of up to 73x for the initial model estimation. Thus, our partitioning and pa
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發(fā)表于 2025-3-29 13:35:55 | 只看該作者
47#
發(fā)表于 2025-3-29 17:20:31 | 只看該作者
48#
發(fā)表于 2025-3-29 20:18:04 | 只看該作者
Regular Path Queries on Large Graphssing rare labels, i.e., elements of the query with few matches, as way-points. A search thereby is decomposed into a set of smaller search problems which are tackled in a bi-directional fashion, supported by a set of graph indexes. Comparison of our algorithm with two approaches following the tradit
49#
發(fā)表于 2025-3-30 02:40:17 | 只看該作者
On the Efficiency of Estimating Penetrating Rank on Large Graphsverage the random sampling approach to . compute P-Rank in . time with provable accuracy guarantees. The empirical results on both real and synthetic datasets show that our approaches achieve high time efficiency with controlled error and outperform the baseline algorithms by at least one order of m
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發(fā)表于 2025-3-30 07:28:02 | 只看該作者
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