Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Marcos Aurélio Domingues"'
Autor:
Camila Vaccari Sundermann, Marcos Aurélio Domingues, Roberta Akemi Sinoara, Ricardo Marcondes Marcacini, Solange Oliveira Rezende
Publikováno v:
Information, Vol 10, Iss 2, p 42 (2019)
Recommender systems help users by recommending items, such as products and services, that can be of interest to these users. Context-aware recommender systems have been widely investigated in both academia and industry because they can make recommend
Externí odkaz:
https://doaj.org/article/e2fbc3d63f344eea8f6b22dd3c807ace
Autor:
Marcos Aurélio Domingues
Publikováno v:
Biblioteca Digital de Teses e Dissertações da USPUniversidade de São PauloUSP.
Mineração de Dados é um processo de natureza iterativa e interativa responsável por identificar padrões em grandes conjuntos de dados, objetivando extrair conhecimento válido, útil e inovador a partir desses. Em Mineração de Dados, Regras de
Publikováno v:
Proceedings of the Brazilian Symposium on Multimedia and the Web.
Publikováno v:
Anais Estendidos do XXVIII Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia 2022).
In this paper, we present a benchmark of several session-based, session-based with reminders and session-aware recommender systems that can be used to improve legal document recommendation in Jusbrasil, the largest legal search engine in Brazil. We f
Autor:
Luis García-Santander, Marcos Aurélio Domingues, Dante Carrizo, Fernando Ulloa-Vásquez, Diego Issicaba, Lucas Melo, Ana-Maria Dumitrescu, Anna Mutule
Publikováno v:
Energies, Vol 14, Iss 4310, p 4310 (2021)
Energies; Volume 14; Issue 14; Pages: 4310
Energies; Volume 14; Issue 14; Pages: 4310
One of the main challenges in smart city models is consumer behaviour, namely guiding the efforts to promote optimal use of energy in the dynamics of the developing cities, through lower energy consumption without impact on the comfort level. This re
Publikováno v:
Information Management and Big Data ISBN: 9783030762278
SIMBig
SIMBig
Day by day, online content delivery services suppliers grow the volume of data on the internet. Music streaming services are one of those services that increase the number of users every day, as well as the number of songs in their catalog. To help t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ef7b50996b2b72d0db332f382829d60
https://doi.org/10.1007/978-3-030-76228-5_22
https://doi.org/10.1007/978-3-030-76228-5_22
Publikováno v:
Anais Estendidos do XXVI Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia 2020).
Big companies usually have human and financial resources to personalize their websites. On the other hand, small and medium-sized companies usually do not have such resources. In this paper we propose ALARM: A Light Application for Recommendation and
Autor:
Vitor Rodrigues Tonon, Camila Vaccari Sundermann, Ricardo Marcondes Marcacini, Renan de Padua, Solange Oliveira Rezende, Marcos Aurélio Domingues
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Publikováno v:
IWSSIP
Personalized music systems usually rely on manual song annotations (tags) as a mechanism for querying and navigating large music collections. However, the manual annotation is a hard task given the large amount of music available nowadays. Automatic