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Titlebook: Recent Challenges in Intelligent Information and Database Systems; 15th Asian Conferenc Ngoc Thanh Nguyen,Siridech Boonsang,Ali Selamat Con

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21#
發(fā)表于 2025-3-25 05:56:15 | 只看該作者
A Novel Method for?Spam Call Detection Using Graph Convolutional Networksefficient and cost-effective method to construct a large, labeled spam detection graph by leveraging end-user collaboration; ii) We propose a graph neural network (GNN)-based model for the spam detection task. Our experiments show that our model outperforms strong baseline models in this research field.
22#
發(fā)表于 2025-3-25 10:10:24 | 只看該作者
23#
發(fā)表于 2025-3-25 14:46:13 | 只看該作者
1865-0929 S 2023, held in Phuket, Thailand, during July 24–26, 2023..The 50 full papers included in this book were carefully reviewed and selected from 224 submissions. They were organized in topical sections as follows: Computer Vision, Cybersecurity and Fraud Detection, Data Analysis, Modeling, and Processi
24#
發(fā)表于 2025-3-25 19:54:23 | 只看該作者
25#
發(fā)表于 2025-3-25 21:29:21 | 只看該作者
The Completion of?a?Smart Factory Research Project by?Concluding a?DAOthe nature of the social movement to the scientific project, and write the relationships between stakeholders and decision-making into the programming code? To answer this question, we present the state of the law related to DAOs and review the literature on whether the direction to apply this type of solution in smart factories is appropriate.
26#
發(fā)表于 2025-3-26 01:20:28 | 只看該作者
27#
發(fā)表于 2025-3-26 05:59:32 | 只看該作者
Obfuscated Malware Detection: Impacts on Detection Methodss offered, along with an empirical examination of malware detection performance assessment to battle obfuscated malware. Overall, this paper highlights the importance of staying ahead of the constantly evolving threat landscape to safeguard computer networks and systems.
28#
發(fā)表于 2025-3-26 10:12:08 | 只看該作者
29#
發(fā)表于 2025-3-26 14:30:33 | 只看該作者
30#
發(fā)表于 2025-3-26 20:19:18 | 只看該作者
Group Trip Planning Approach with Travel Time and Ratio Constraints best fits for the group preferences under the group constraints. The experimental results show that our proposed approach performs well under various group constraints and is greatly better than the algorithm extended by the single-user trip planning algorithm.
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