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Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2017; 18th International C Hujun Yin,Yang Gao,Minling Zhang Conference proceedi

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41#
發(fā)表于 2025-3-28 18:32:46 | 只看該作者
Dynamic Community Detection Algorithm Based on Automatic Parameter Adjustment,troduced. The proposed algorithm can choose to satisfy or ignore the optional parameter by judging whether it is reasonable. Our algorithm also eliminates the existing fragments. A delicate pruning is designed for fast determination. Experiments show that our mAttractor outperforms Attractor by 2%–2
42#
發(fā)表于 2025-3-28 22:26:51 | 只看該作者
43#
發(fā)表于 2025-3-29 02:10:57 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/469587.jpg
44#
發(fā)表于 2025-3-29 03:21:41 | 只看該作者
45#
發(fā)表于 2025-3-29 07:46:01 | 只看該作者
46#
發(fā)表于 2025-3-29 14:24:52 | 只看該作者
https://doi.org/10.1007/978-3-319-68935-7Applied computing; Artificial intelligence; Bioinformatics; Computing methodologies; Data management sys
47#
發(fā)表于 2025-3-29 16:49:23 | 只看該作者
48#
發(fā)表于 2025-3-29 23:34:10 | 只看該作者
Dynamic Community Detection Algorithm Based on Automatic Parameter Adjustment, scalable algorithms are drawing more attention. Among those methods, the algorithm named Attractor is quite outstanding both in terms of accuracy and scalability. However, it is highly dependent on the parameter, which is abstract for users. The improper parameter value can bring about some problem
49#
發(fā)表于 2025-3-29 23:56:43 | 只看該作者
50#
發(fā)表于 2025-3-30 04:33:48 | 只看該作者
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