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Titlebook: Database and Expert Systems Applications; 34th International C Christine Strauss,Toshiyuki Amagasa,Ismail Khalil Conference proceedings 202

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樓主: 厭氧
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發(fā)表于 2025-3-23 13:35:47 | 只看該作者
https://doi.org/10.1007/978-3-658-31316-6 are not free from errors, which include among others wrong and missing values as well as duplicates. Data deduplication has received a lot of attention from the research community. The research efforts have resulted in a state-of-the-art data deduplication pipeline, supported by software tools and
12#
發(fā)表于 2025-3-23 14:24:47 | 只看該作者
Allgemeiner Managementkreislaufuerying semantic evolved data, which conciliate the multiple versions the data may have. An implementation of the model and algorithms, MellowDB, was developed, and its performance was analyzed, showing the proposed algorithms and model are feasible.
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發(fā)表于 2025-3-23 22:05:27 | 只看該作者
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發(fā)表于 2025-3-23 23:53:50 | 只看該作者
Timothy Kaufmann,Karsten Oehlers to launch tuning requests periodically, yet resource-intensive tuning sessions can obstruct it, particularly when dealing with frequently varying workloads..To tackle this challenge, we propose a learned tuning diagnostic that can be incorporated into the . paradigm for online index tuning. Rather
15#
發(fā)表于 2025-3-24 05:39:08 | 只看該作者
Controlling mit der SAP Analytics Cloudmulti-dimensional data applications are generally data-intensive, array databases can benefit from multi-processing systems to improve performance. However, when dealing with Non-Uniform Memory Access (NUMA) machines, the movement of massive amounts of data across NUMA nodes may result in significan
16#
發(fā)表于 2025-3-24 09:05:10 | 只看該作者
https://doi.org/10.34157/978-3-648-17372-5mework of LDP, before they are transmitted to the server. This technology can be applied to various data types, including key-value data. However, in existing LDP mechanisms for key-value data, it is difficult to balance data utility and communication costs, particularly when the domain of keys is l
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發(fā)表于 2025-3-24 11:03:18 | 只看該作者
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發(fā)表于 2025-3-24 18:24:43 | 只看該作者
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發(fā)表于 2025-3-24 21:55:48 | 只看該作者
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發(fā)表于 2025-3-24 23:42:29 | 只看該作者
Effective and?Efficient Heuristic Algorithms for?Supporting Optimal Location of?Hubs over?Networks won of the mathematical model that we carved to fit the operational needs of .. Afterwards, we propose . able to solve the problem in a faster way with .. The heuristic algorithms proposed in our framework progressively reach a good approximation of the solution. Experimental results confirm the benefits of our approach.
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