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Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series; 28th International C Igor V. Tetko,Věra K?rková,Fabian

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發(fā)表于 2025-3-25 06:11:52 | 只看該作者
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發(fā)表于 2025-3-25 21:17:58 | 只看該作者
https://doi.org/10.1007/978-981-19-2669-3methods achieved improvement by capturing user and product information. However, these methods fail to incorporate user preferences and product characteristics reasonably and effectively. What’s more, these methods all only use the explicit influences observed in texts and ignore the implicit intera
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發(fā)表于 2025-3-26 01:47:43 | 只看該作者
Quantum Bonding Motion, Continued Future sentiment in text data. We observe that humans often express transitional emotion between two adjacent discourses with discourse markers like “but”, “though”, “while”, etc., and the head discourse and the tail discourse usually indicate opposite emotional tendencies. Based on this observation, we p
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發(fā)表于 2025-3-26 15:30:16 | 只看該作者
Materials Integration Strategies,has become a powerful strategy. Mid roll ads are the video ads that are played between the content of a video being watched by the user. While a lot of research has already been done in the field of analyzing the context of the video to suggest relevant ads, little has been done in the field of effe
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發(fā)表于 2025-3-26 18:00:15 | 只看該作者
Materials Integration Strategies,ks on the collaborative filtering problem in item recommendation, most of the existing methods employ a similar loss function, i.e., the prediction loss of user-item interactions, and only change the form of the input, which may limit the model’s performance. To address this problem, we present a no
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