Idioma:

EXEHDA-RR: Machine Learning and MCDA with Semantic Web in IoT Resources Classification

Dilli, Renato ; Filho, Huberto Kaiser ; Pernas, Ana Marilza ; Yamin, Adenauer

Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web, 2017, p.293-300

Texto completo disponível

Citações Citado por

Título:
EXEHDA-RR: Machine Learning and MCDA with Semantic Web in IoT Resources Classification
Autor: Dilli, Renato ; Filho, Huberto Kaiser ; Pernas, Ana Marilza ; Yamin, Adenauer
Assuntos: Software and its engineering -- Software organization and properties -- Contextual software domains -- Software infrastructure -- Middleware
É parte de: Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web, 2017, p.293-300
Descrição: Currently, a lot of resources are connected to the Internet, many simultaneously requesting and providing services. The adequate selection of resources that best meet the demands of users with a broad range of options has been a relevant and current research challenge. Based on the non-functional parameters of QoS play a significant role in the ranking of these resources according to the services they offer. This paper aims to aggregate machine learning in the pre-classification of EXEHDA middleware resources, to reduce the computational cost generated by MCDA algorithms. We presented the proposed software architecture (EXEHDA-RR), and the obtained results with the integration of machine learning in the classification process are promissing, and indicate to the research continuation.
Títulos relacionados: ACM Other Conferences
Editor: New York, NY, USA: ACM
Idioma: Inglês

Voltar para lista de resultados

Anterior Resultado 5 Avançar Ir para próxima página