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Titlebook: Uncertainty Reasoning for the Semantic Web III; ISWC International W Fernando Bobillo,Rommel N. Carvalho,Michael Pool Conference proceeding

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發(fā)表于 2025-3-23 12:21:38 | 只看該作者
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發(fā)表于 2025-3-23 17:12:52 | 只看該作者
Graph-Based Regularization for Transductive Class-Membership Prediction,ve inference may be limiting. This work proposes a new method for similarity-based class-membership prediction in Description Logic knowledge bases. The underlying idea is based on the concept of . class-membership information among similar individuals; it is non-parametric in nature and characteriz
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發(fā)表于 2025-3-23 21:08:26 | 只看該作者
Analyzing User Demographics and User Behavior for Trust Assessment,ion of trust can be tackled from a variety of other perspectives. In this chapter, we model trust relying on user reputation, user demographics and from provenance. We then explore the effects of combining trust computed through these different methods. Concretely, the first contribution of this cha
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發(fā)表于 2025-3-24 01:33:38 | 只看該作者
Bridging Gaps Between Subjective Logic and Semantic Web,tually benefit from each other, since subjective logic is useful to handle the inner noisiness of the Semantic Web data, while the Semantic Web offers a means to obtain evidence useful for performing evidential reasoning based on subjective logic. In this chapter we describe three extensions and app
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發(fā)表于 2025-3-24 03:21:51 | 只看該作者
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發(fā)表于 2025-3-24 08:32:09 | 只看該作者
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發(fā)表于 2025-3-24 17:47:15 | 只看該作者
Conference proceedings 2014URSW), held at the International Semantic Web Conferences (ISWC) in 2011, 2012, and 2013. The 16 papers presented were carefully reviewed and selected from numerous submissions. The papers included in this volume are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy an
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發(fā)表于 2025-3-24 22:56:23 | 只看該作者
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發(fā)表于 2025-3-25 01:42:31 | 只看該作者
Graph-Based Regularization for Transductive Class-Membership Prediction,ed by interesting complexity properties, making it a potential candidate for large-scale transductive inference. We also evaluate its effectiveness with respect to other approaches based on inductive inference in SW literature.
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