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Titlebook: Database and Expert Systems Applications; 32nd International C Christine Strauss,Gabriele Kotsis,Ismail Khalil Conference proceedings 2021

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樓主: industrious
31#
發(fā)表于 2025-3-27 00:12:47 | 只看該作者
Medical-Based Text Classification Using FastText Features and CNN-LSTM Model as CNN, support vector machines, decision trees, naive Bayes, and K-nearest neighbor. The performance of all used models were evaluated in terms of accuracy, precision, recall, and F1 score. The CNN-LSTM outperforms all other models in terms of all evaluation parameters and achieved 86.34%, 90.68%,
32#
發(fā)表于 2025-3-27 02:31:41 | 只看該作者
33#
發(fā)表于 2025-3-27 06:11:44 | 只看該作者
34#
發(fā)表于 2025-3-27 12:07:11 | 只看該作者
Reference Architecture for Running Large Scale Data Integration ExperimentsThis paper contributes a reference architecture of a reusable infrastructure for scientific experiments on data processing and data integration. The architecture is based on containerization and is integrated with an external machine learning cloud service to build performance models.
35#
發(fā)表于 2025-3-27 16:50:45 | 只看該作者
36#
發(fā)表于 2025-3-27 20:20:24 | 只看該作者
37#
發(fā)表于 2025-3-27 23:40:16 | 只看該作者
Ariane von Raesfeld,Elly van der Helmve thousands to millions of tables, but often have missing or incorrect labels for rows (or columns) with attribute names (e.g. .). Missing or incorrect metadata labels [.] prevent or at least significantly complicate the fundamental data management tasks such as ., and many other. Different sources
38#
發(fā)表于 2025-3-28 05:46:05 | 只看該作者
39#
發(fā)表于 2025-3-28 08:15:37 | 只看該作者
https://doi.org/10.1007/978-3-030-17963-2roposed to identify the source data from which the analysis results are derived, analysis is becoming increasingly complex both with regard to the target (e.g., images, videos, and texts) and technology (e.g., AI and machine learning). In such complex data analysis, simply showing the source data ma
40#
發(fā)表于 2025-3-28 13:11:14 | 只看該作者
Eduardo Rivera-López,Martin Heviahe Green Solow model, a neoclassical economics model for sustainable growth. Faced with the challenges posed by the coupling of the equations, the scarcity of data, and their auto-correlation, we devise several solutions. We present a baseline model and propose three models leveraging neural ordinar
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