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Titlebook: Advances in Data and Web Management; Joint International Qing Li,Ling Feng,Qiao-Ming Zhu Conference proceedings 2009 Springer-Verlag Berli

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樓主: FLAW
41#
發(fā)表于 2025-3-28 15:23:49 | 只看該作者
The Fable of the Educational Manager,criterion for determining the .NNs is the shortest network distance between objects. We first highlight the limitations of the existing approaches, and then propose a cost-effective algorithm, namely the ., to overcome these limitations. Comprehensive experiments are conducted to demonstrate the efficiency of the proposed approach.
42#
發(fā)表于 2025-3-28 18:59:43 | 只看該作者
The Microbial Diversity of Cavesibutes and explain how we rank the web page based on these attributes. The experiment result shows that our proposed algorithm can promote the pages with a higher delivery quality to higher positions in the result list. We also compare several rank aggregation algorithms trying to find out the best performing one.
43#
發(fā)表于 2025-3-29 02:26:25 | 只看該作者
https://doi.org/10.1007/978-3-642-00672-2data analysis; data mining; database; indexing; information engineering; information management; ip filter
44#
發(fā)表于 2025-3-29 04:28:32 | 只看該作者
978-3-642-00671-5Springer-Verlag Berlin Heidelberg 2009
45#
發(fā)表于 2025-3-29 08:27:17 | 只看該作者
https://doi.org/10.1007/978-3-642-97491-5tood, the same is not true in a scenario where the data is spread across multiple nodes in a distributed system. Since the size of XML data collections are increasing along with the heavy workloads that need to be evaluated on top of these collections, scaling a centralized solution is becoming incr
46#
發(fā)表于 2025-3-29 12:20:46 | 只看該作者
47#
發(fā)表于 2025-3-29 18:28:18 | 只看該作者
48#
發(fā)表于 2025-3-29 20:28:51 | 只看該作者
49#
發(fā)表于 2025-3-30 02:54:13 | 只看該作者
50#
發(fā)表于 2025-3-30 07:29:58 | 只看該作者
The Fable of the International Provider, data to make decisions. Traditional query systems do not factor in data quality considerations in their response. Studies into the diverse interpretations of data quality indicate that fitness for use is a fundamental criteria in the evaluation of data quality. In this paper, we present a 4 step me
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