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Titlebook: Big Data Analytics; 10th International C Partha Pratim Roy,Arvind Agarwal,R. Uday Kiran Conference proceedings 2022 The Editor(s) (if appli

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發(fā)表于 2025-3-25 07:15:23 | 只看該作者
22#
發(fā)表于 2025-3-25 08:52:11 | 只看該作者
23#
發(fā)表于 2025-3-25 15:19:23 | 只看該作者
R. B. Gerber,Victoria Buch,Mark A. Ratnerting of the selected core node. We have demonstrated here that our algorithm finds meaningful hierarchical communities in real-world data sets. We have also evaluated the effects of the PageRank of the core node and the PageRank threshold parameter for the nodes included in its communities.
24#
發(fā)表于 2025-3-25 16:11:23 | 只看該作者
Qiuhong Xiong,Zhenjie Zhou LL.M, PhDRP. It utilizes a novel Pair Support Pruning (PSP) optimization to reduce the search space. Experiments show that FastTIRP outperforms the state-of-the-art VertTIRP algorithm in terms of runtime on four benchmark datasets.
25#
發(fā)表于 2025-3-25 21:56:53 | 只看該作者
26#
發(fā)表于 2025-3-26 01:54:47 | 只看該作者
Community Detection in?Large Directed Graphsting of the selected core node. We have demonstrated here that our algorithm finds meaningful hierarchical communities in real-world data sets. We have also evaluated the effects of the PageRank of the core node and the PageRank threshold parameter for the nodes included in its communities.
27#
發(fā)表于 2025-3-26 06:52:46 | 只看該作者
FastTIRP: Efficient Discovery of?Time-Interval Related PatternsRP. It utilizes a novel Pair Support Pruning (PSP) optimization to reduce the search space. Experiments show that FastTIRP outperforms the state-of-the-art VertTIRP algorithm in terms of runtime on four benchmark datasets.
28#
發(fā)表于 2025-3-26 10:17:32 | 只看該作者
29#
發(fā)表于 2025-3-26 15:02:06 | 只看該作者
Conference proceedings 2022ntains 4 keynote talks in full-paper length. The papers are organized in the following topical sections: Big Data Analytics: Vision and Perspectives; Data Science: Architectures; Data Science: Applications; Graph Analytics; Pattern Mining; Predictive Analytics in Agriculture..
30#
發(fā)表于 2025-3-26 16:56:56 | 只看該作者
https://doi.org/10.1007/978-3-658-19928-9rvice identification. The motivation arises from the fact that no such dataset is available in public domain, and very minimal work has been done on automated service identification from requirements documents.
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