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Titlebook: Computational Collective Intelligence. Technologies and Applications; 4th International Co Ngoc-Thanh Nguyen,Kiem Hoang,Piotr J?drzejowicz

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21#
發(fā)表于 2025-3-25 07:15:03 | 只看該作者
https://doi.org/10.1007/978-1-4899-1615-0pment phases. In particular, the testing and debugging phases, more precisely, how to chose those tests more suitable to be applied, is simplified since tests are automatically extracted from the specification.
22#
發(fā)表于 2025-3-25 08:38:04 | 只看該作者
https://doi.org/10.1007/978-3-8349-9809-5 with the Share-Per-Link(SPL) architecture where partial wavelength converters are distributed at each output port. A continuous-time Markov chain model is proposed to analyze the performance of OBS core nodes operated with the deflection routing rule.
23#
發(fā)表于 2025-3-25 14:04:02 | 只看該作者
24#
發(fā)表于 2025-3-25 19:29:46 | 只看該作者
OCE: An Online Colaborative Editorpment phases. In particular, the testing and debugging phases, more precisely, how to chose those tests more suitable to be applied, is simplified since tests are automatically extracted from the specification.
25#
發(fā)表于 2025-3-25 23:55:53 | 只看該作者
26#
發(fā)表于 2025-3-26 01:25:44 | 只看該作者
0302-9743 proceedings of the 4th International Conference on Computational Collective Intelligence, ICCCI, held in Ho Chi Minh City, Vietnam, in November 2012..The 113 revised full papers presented were carefully reviewed and selected from 397 submissions. The papers are organized in topical sections on (Par
27#
發(fā)表于 2025-3-26 06:06:52 | 只看該作者
Tarski, Truth, and Natural Languages of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M2l is outperformed at least at 2 orders of magnitudes against the benchmarked FP-Growth.
28#
發(fā)表于 2025-3-26 11:55:34 | 只看該作者
29#
發(fā)表于 2025-3-26 12:56:51 | 只看該作者
EFP-M2: Efficient Model for Mining Frequent Patterns in Transactional Database of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M2l is outperformed at least at 2 orders of magnitudes against the benchmarked FP-Growth.
30#
發(fā)表于 2025-3-26 18:52:19 | 只看該作者
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