Ontology Based Suggestion Distribution System

Chung, Tong Lee; Xu, Bin; Yao, Xiaoling; Li, Qi; Yuan, Bozhi

doi:10.1007/978-3-319-15615-6_31

Cited by 1 publication

(3 citation statements)

References 9 publications

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“…Other works do not focus on diagnosing but on patient assistance and particularly eldercare [27,42]. In these works, the goal is not to detect whether the patient suffers or not from a specific disease, but to monitor and help them to conduct everyday tasks.…”

Section: Ambient Intelligence Applications On Particular Domainsmentioning

confidence: 99%

“…However, most of the works considered aim for citizen query [27,31,38]. In Santos et al [38], a city KG is generated such as dashboards can be automatically built upon to monitor the urban environment.…”

Section: Ambient Intelligence Applications On Particular Domainsmentioning

confidence: 99%

“…In Santos et al [38], a city KG is generated such as dashboards can be automatically built upon to monitor the urban environment. Chung et al [27] present an assistant system for distributing citizen complaints to their adequate city departments.…”

Section: Ambient Intelligence Applications On Particular Domainsmentioning

confidence: 99%

See 2 more Smart Citations

Prediction and Decision-Making in Intelligent Environments Supported by Knowledge Graphs, A Systematic Review

Amador-Domínguez

Serrano

Paz

2019

Sensors

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Ambient Intelligence is currently a lively application domain of Artificial Intelligence and has become the central subject of multiple initiatives worldwide. Several approaches inside this domain make use of knowledge bases or knowledge graphs, both previously existing and ad hoc. This form of representation allows heterogeneous data gathered from diverse sources to be contextualized and combined to create relevant information for intelligent systems, usually following higher level constraints defined by an ontology. In this work, we conduct a systematic review of the existing usages of knowledge bases in intelligent environments, as well as an in-depth study of the predictive and decision-making models employed. Finally, we present a use case for smart homes and illustrate the use and advantages of Knowledge Graph Embeddings in this context.

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Section: Ambient Intelligence Applications On Particular Domainsmentioning

confidence: 99%