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Titlebook: Big Data; 7th CCF Conference, Hai Jin,Xuemin Lin,Yihua Huang Conference proceedings 2019 Springer Nature Singapore Pte Ltd. 2019 artificia

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31#
發(fā)表于 2025-3-27 00:25:56 | 只看該作者
Research of CouchDB Storage Plugin for Big Data Query Engine Apache Drillcurity and usability of MongoDB, Apache Drill is limited in querying and processing document data. CouchDB is an emerging document-oriented database. Compared to MongoDB, CouchDB has the advantage of supporting triggers, running in Android and BSD environments, rendering in JSON format, and supporti
32#
發(fā)表于 2025-3-27 02:14:21 | 只看該作者
Text, Speech and Language Technologyis, the amount of data involved and the distance of the node network which service involved, which can reduce the network overhead and improve execution efficiency. Finally, the effectiveness of the proposed method is verified by experimental comparison.
33#
發(fā)表于 2025-3-27 08:58:38 | 只看該作者
34#
發(fā)表于 2025-3-27 11:08:28 | 只看該作者
35#
發(fā)表于 2025-3-27 17:07:19 | 只看該作者
A Phonological Model of French Intonationg the occurrence rule of different product features in reviews, we propose a novel product similarity calculation, which also performs weighted fusion based on information entropy with a variety of general similarity calculation methods. Finally, compared with traditional methods, the experimental r
36#
發(fā)表于 2025-3-27 20:33:50 | 只看該作者
A Taxonomic Analysis of Hungarian Intonatione into k discrete intervals. We verficate the distributed discretization performance in the preprocessing of random forest, Bayes and multilayer perceptron classification on real sensor big data sets. Experimental results show that the time performance and classification accuracy of the distributed
37#
發(fā)表于 2025-3-27 22:37:14 | 只看該作者
Intonation, Paralanguage, Prosodyerform the easier and concurrent linear calculations in parallel. Different from the physical division in model parallelism, the logical split based on hidden neurons can greatly reduce the communication overhead which is a major bottleneck in distributed training. We evaluate the effectiveness of t
38#
發(fā)表于 2025-3-28 03:15:50 | 只看該作者
39#
發(fā)表于 2025-3-28 09:02:34 | 只看該作者
Thomas Thurnell-Read,Mark Monaghan. The experiments show that the above methods are effective in dealing with large scale social network graph problem and these methods can effectively solve the problem of privacy leakage of subgraph matching.
40#
發(fā)表于 2025-3-28 10:41:45 | 只看該作者
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