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Titlebook: ECML PKDD 2020 Workshops; Workshops of the Eur Irena Koprinska,Michael Kamp,Jon Atle Gulla Conference proceedings 2020 Springer Nature Swit

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樓主: EVOKE
51#
發(fā)表于 2025-3-30 12:14:27 | 只看該作者
52#
發(fā)表于 2025-3-30 13:48:54 | 只看該作者
53#
發(fā)表于 2025-3-30 19:09:13 | 只看該作者
A Hybrid Recommendation System Based on Bidirectional Encoder Representationsad item descriptions during online shopping, which contain key information about the item and its features. However the item descriptions are in unstructured form and using them in the deep learning model is a problem. In this study, we integrate a pioneering Natural Language Processing technique in
54#
發(fā)表于 2025-3-30 22:45:42 | 只看該作者
Leveraging Multi-target Regression for Predicting the Next Parallel Activities in Event Logsdicting the activity that will be executed as the next step during process execution. However, traditional algorithms do not cope with the presence of parallel activities, thus failing to devise accurate prediction of multiple parallel activities that will be simultaneously executed. Moreover, they
55#
發(fā)表于 2025-3-31 03:54:44 | 只看該作者
The Euthyphro Problem Revisited,is close to the law and order stance. Far from offering a political judgment of value, the aim of the paper is to raise awareness about the potential implicit, and often overlooked, political assumptions and political values that may be undergirding a decision that is apparently purely technical.
56#
發(fā)表于 2025-3-31 08:20:17 | 只看該作者
57#
發(fā)表于 2025-3-31 10:59:07 | 只看該作者
https://doi.org/10.1007/978-3-662-07167-0ology, in which multi-target regression is used to predict the next parallel activities in event logs without the need of aligning traces during process executions. Experimental results show that the proposed solution achieve more accurate predictions compared to the single-target setting.
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