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The evolution of Knowledge Graphs (KGs), during the last two decades, has encouraged developers to create more and more context related KGs. This advance is extremely important because Artificial Intelligence (AI) applications can access open domain specific information in a semantically rich, machine understandable format. In this paper, we present the MindSpaces KG, a KG that can represent emotions-relevant and functional design for the indoor and urban adaptive design. The MindSpaces KG can integrate emotional, physiological, visual, and textual measurements, for the development of online adapting environments. Moreover, we present a reasoning mechanism that extracts crucial knowledge from the MindSpaces KG, which can help users in real-life scenarios. The scenarios were provided by experts.
Knowledge Graph, Ontology, Reasoning Mechanism, Indoor/Urban Adaptive Design, Semantic Web
Knowledge Graph, Ontology, Reasoning Mechanism, Indoor/Urban Adaptive Design, Semantic Web
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