quick-relievers
发表于 2025-3-21 17:51:08
书目名称Data Stream Management影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0263155<br><br> <br><br>书目名称Data Stream Management读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0263155<br><br> <br><br>
Arteriography
发表于 2025-3-21 20:40:21
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Condyle
发表于 2025-3-22 01:34:15
Quantiles and Equi-depth Histograms over Streams the 99-percentile, or the quartiles of a set are examples of quantile queries. Many database optimization problems involve approximate quantile computations over large data sets. Query optimizers use quantile estimates to estimate the size of intermediate results and choose an efficient plan among
转向
发表于 2025-3-22 08:10:17
Join Sizes, Frequency Moments, and Applicationslem is at the heart of a wide variety of other problems, both in databases/data streams and beyond, including approximating range-query aggregates, quantiles, and heavy-hitter elements, and building approximate histograms and wavelet representations. Our discussion focuses on efficient, sketch-based
JUST
发表于 2025-3-22 09:13:50
Top-, Frequent Item Maintenance over Streamsthat occur most frequently in one pass over the data stream using a small amount of storage space. Such problems arise in a variety of settings. For example, a search engine might be interested in gathering statistics about its query stream and in particular, identifying the most popular queries. An
等待
发表于 2025-3-22 16:33:30
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等待
发表于 2025-3-22 20:56:24
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光滑
发表于 2025-3-22 22:31:53
Clustering Data Streamsch that, under some definition of “similarity,” similar items are in the same group and dissimilar items are in different groups. In this chapter we focus on clustering in a streaming scenario where a small number of data items are presented at a time and we cannot store all the data points. Thus, o
规章
发表于 2025-3-23 01:54:38
Mining Decision Trees from Streams. Mining these continuous data streams brings unique opportunities, but also new challenges. We present a method that can semi-automatically enhance a wide class of existing learning algorithms so they can learn from such high-speed data streams in real time. The method works by sampling just enough
Accessible
发表于 2025-3-23 05:56:25
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