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Titlebook: VipIMAGE 2017; Proceedings of the V Jo?o Manuel R.S. Tavares,R.M. Natal Jorge Conference proceedings 2018 Springer International Publishing

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樓主: 淺吟低唱
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發(fā)表于 2025-3-23 10:29:38 | 只看該作者
J. Oliveira,R. Parafita,S. Branco rules in writing systems, especially Tunisian Dialectical (TD) which presents an undertaking challenge due to its complexity, ambiguity, the morphological richness of the language, the absence of contextual information, the code-switching (CS) and mostly the multilingualism phenomena in textual pro
12#
發(fā)表于 2025-3-23 16:58:30 | 只看該作者
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發(fā)表于 2025-3-23 21:06:49 | 只看該作者
Lenka Bódiová,Ond?ej Tichy,Václav ?mídlThis explosion had been expressing by an exponential growth of data volume among the low-quality information. This paper is designed to provide detailed information about some intellectual tools which are support decision taking by automatic knowledge extraction. In the first part of paper, we consi
14#
發(fā)表于 2025-3-24 02:04:41 | 只看該作者
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發(fā)表于 2025-3-24 03:11:23 | 只看該作者
Pedro Costa,Helder Freitas,Filomena Soares,Jo?o Sena Estevesgraph (KG) in the metaphor of a brain, the ViewpointS approach attempts to trace and assess the dynamics of collaborative knowledge building. Our approach relies on a bipartite graph of resources (agents, documents, topics) and time stamped “viewpoints” emitted by human or artificial agents. These v
16#
發(fā)表于 2025-3-24 09:32:04 | 只看該作者
P. Bibiloni,M. González-Hidalgo,S. Massanet,A. Mir,D. Ruiz-Aguilera the color of the ink used to print those names. The results of the Stroop test used in our experiment were analyzed from the point of view of human cognitive load. 62 volunteers took part in a study conducted on the iMotions biometric platform in laboratory conditions. Data were collected using obs
17#
發(fā)表于 2025-3-24 12:32:28 | 只看該作者
Danilo Samuel Jodas,Aledir Silveira Pereira,Jo?o Manuel R. S. Tavaresemantic interactions between users and items in the database, thereby increasing customer satisfaction and revenue. Furthermore, collaborative filtering research has significantly advanced in recent years with the compelling expressiveness of graph-based neural networks. In this paper, we introduce
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發(fā)表于 2025-3-24 17:15:40 | 只看該作者
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發(fā)表于 2025-3-24 19:50:11 | 只看該作者
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發(fā)表于 2025-3-25 01:20:11 | 只看該作者
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