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Titlebook: AI 2010: Advances in Artificial Intelligence; 23rd Australasian Jo Jiuyong Li Conference proceedings 2011 The Editor(s) (if applicable) and

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發(fā)表于 2025-3-28 15:27:42 | 只看該作者
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發(fā)表于 2025-3-28 21:27:09 | 只看該作者
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發(fā)表于 2025-3-29 02:26:23 | 只看該作者
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發(fā)表于 2025-3-29 04:07:04 | 只看該作者
High-Voltage and High-Current Injuries, setup controlled experiments for different term ranking methods. Reuter-21578 text corpus is used as the dataset. Two popular classification algorithms SVM and Boostexter are adopted to evaluate the performance of different term ranking methods. Experimental results show that the new term ranking method performs better.
45#
發(fā)表于 2025-3-29 09:20:37 | 只看該作者
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發(fā)表于 2025-3-29 14:23:22 | 只看該作者
0302-9743 tralasian Joint Conference on Artificial Intelligence, AI 2010, held in Adelaide, Australia, in December 2010. The 52 revised full papers presented were carefully reviewed and selected from 112 submissions. The papers are organized in topical sections on knowledge representation and reasoning; data
47#
發(fā)表于 2025-3-29 18:12:46 | 只看該作者
Functional Analysis of Violence–Aggression in the area. It turns out that our generalization of imaging indeed is an account of probabilistic belief erasure as opposed to probabilistic belief contraction. In the process we also examine two other accounts of probabilistic belief removal which are rather novel and difficult to classify under the standard belief change taxonomy.
48#
發(fā)表于 2025-3-29 20:38:57 | 只看該作者
49#
發(fā)表于 2025-3-30 02:43:00 | 只看該作者
Leng Hong Lim,Bradley A. Saville better clusters. Our experimental results show that on average the execution time of Approximate UK-means is only 25% more than K-means and our approach reduces the discrepancies of K-means’ clustering results by more than 70% at most.
50#
發(fā)表于 2025-3-30 05:02:12 | 只看該作者
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