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Titlebook: Digital Libraries and Archives; 8th Italian Research Maristella Agosti,Floriana Esposito,Nicola Ferro Conference proceedings 2013 Springer-

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發(fā)表于 2025-3-23 12:58:53 | 只看該作者
Machine Ethics and Automated Vehiclesty in the archival context. We show how this service allows us to address the interoperability between diversified digital archive and annotation systems. Furthermore, it propels the use of annotations to enhance the user experience and to exploit the archivists expertise both in the description and consultation phases.
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發(fā)表于 2025-3-23 16:59:01 | 只看該作者
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發(fā)表于 2025-3-24 05:59:58 | 只看該作者
Machine Ethics and Automated Vehiclestwork Project EFG (European Film Gateway) provides a single access point to 59 collections from 19 archives and across 14 European countries, for a total of 640,000 digital objects. This paper illustrates challenges and solutions in the realization of the EFG data infrastructure. These mainly concer
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發(fā)表于 2025-3-24 07:04:37 | 只看該作者
https://doi.org/10.1007/978-3-319-05990-7onvergence of two only apparently separated worlds. The aim of this paper is to present a model of collaborative semantic annotation of texts (SemLib project), suggesting a system that find in Semantic Web and Linked Data the solution technologies for enabling structured semantic annotation, also in
17#
發(fā)表于 2025-3-24 12:05:20 | 只看該作者
Machine Ethics and Automated Vehiclesty in the archival context. We show how this service allows us to address the interoperability between diversified digital archive and annotation systems. Furthermore, it propels the use of annotations to enhance the user experience and to exploit the archivists expertise both in the description and
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發(fā)表于 2025-3-24 17:39:38 | 只看該作者
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發(fā)表于 2025-3-24 20:12:19 | 只看該作者
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發(fā)表于 2025-3-25 00:20:37 | 只看該作者
Matteo Oldoni,Siddartha Khastgirssification task from a set of experts to a larger and untrained set of people, the results of the classification are not accurate. The lack of control and guidelines generates noisy tags (i.e. tags without a clear semantic) which lower the precision of the user generated classifications. In order t
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