Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/70415

TítuloImproving performance of recommendation system architecture
Autor(es)Cunha, Gil
Peixoto, Hugo
Machado, José Manuel
Palavras-chaveE-commerce
Recommendation system
Software architecture
Data1-Jan-2020
EditoraSpringer
RevistaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resumo(s)The exponential appearance of online stores has implied higher market competitiveness and, consequently, companies need to adopt certain strategies to obtain greater prominence and gain clientele. This paper explores an architectural approach to incorporate a recommendation system in online stores, in order to offer a solution to achieve those goals. Developing the recommendation system infrastructure with NodeJS, based on a REST API, and according to microservices architecture concepts, has proven to be very efficient when it comes to managing great volumes of requests and data, and be capable to serve multiple tenants within a short response time. Clustering techniques were also implemented to increase the system’s performance and capability of handling requests.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/70415
ISBN978-3-030-62364-7
DOI10.1007/978-3-030-62365-4_47
ISSN0302-9743
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CAlg - Livros e capítulos de livros/Books and book chapters

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