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Titlebook: BNAIC 2016: Artificial Intelligence; 28th Benelux Confere Tibor Bosse,Bert Bredeweg Conference proceedings 2017 Springer International Publ

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樓主: Hypothesis
41#
發(fā)表于 2025-3-28 14:59:44 | 只看該作者
42#
發(fā)表于 2025-3-28 19:12:48 | 只看該作者
SWISH DataLab: A Web Interface for Data Exploration and Analysisibility of the research at any chosen point. Using search logs from the National Library of the Netherlands combined with the collection content metadata, we demonstrate how to use SWISH DataLab for all stages of data analysis, using Prolog predicates, graph visualizations, and R.
43#
發(fā)表于 2025-3-29 00:14:08 | 只看該作者
44#
發(fā)表于 2025-3-29 07:08:37 | 只看該作者
45#
發(fā)表于 2025-3-29 07:35:07 | 只看該作者
46#
發(fā)表于 2025-3-29 12:20:13 | 只看該作者
Matter Radii and Density Distributionsand –to some extent- moral responsibility to the robot. Moreover, we found that a robot’s display of lack of effort does not lead to the level of affective and behavioral reactions of participants normally found in reactions to other human agents.
47#
發(fā)表于 2025-3-29 16:52:12 | 只看該作者
Lack of Effort or Lack of Ability? Robot Failures and Human Perception of Agency and Responsibilityand –to some extent- moral responsibility to the robot. Moreover, we found that a robot’s display of lack of effort does not lead to the level of affective and behavioral reactions of participants normally found in reactions to other human agents.
48#
發(fā)表于 2025-3-29 20:12:23 | 只看該作者
Predicting Civil Unrest by Categorizing Dutch Twitter Events in social media streams is challenging due to the large number and variety of messages that are posted. The early detection of future social events, specifically those associated with civil unrest, has a wide applicability in areas such as security, e-governance, and journalism. We used machine lea
49#
發(fā)表于 2025-3-30 02:51:40 | 只看該作者
50#
發(fā)表于 2025-3-30 07:45:59 | 只看該作者
Extracting Core Claims from Scientific Articlesof this, it becomes increasingly difficult to keep up with the latest developments in a scientific field. To address this problem, we present here an approach to help researchers learn about the latest developments and findings by extracting in a normalized form core claims from scientific articles.
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