Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Adriano C. M. Pereira"'
Publikováno v:
Journal of Internet Services and Applications, Vol 10, Iss 1, Pp 1-15 (2019)
Abstract The competitive dynamics of the globalized market demand information on the internal and external reality of corporations. Information is a precious asset and is responsible for establishing key advantages to enable companies to maintain the
Externí odkaz:
https://doaj.org/article/8174cbcc97764b54a362885755734aa3
Publikováno v:
Revista Brasileira de Computação Aplicada, Vol 11, Iss 1, Pp 36-47 (2019)
Atualmente grandes volumes de dados são gerados e coletados por meio de sensores, dispositivos e redes sociais. A capacidade de lidar com grandes massas de dados tornou-se um importante fator para o sucesso de muitas organizações, exigindo, cada v
Externí odkaz:
https://doaj.org/article/35155c8dceaf41acbad0a24809f826d1
Publikováno v:
Revista Brasileira de Computação Aplicada, Vol 10, Iss 2, Pp 54-63 (2018)
This paper proposes a combined approach of two machine learning techniques for financial time series classification. Boltzmann Restricted Machines (RBM) were used as the latent features extractor and Support Vector Machines (SVM) as the classifier. T
Externí odkaz:
https://doaj.org/article/10bc49c9339e4b898dbb8093d1c6a6b6
Publikováno v:
Information Sciences. 512:1078-1102
Sentiment analysis has become a key tool for several social media applications, including, analysis of user’s opinions about products and services, support for politics during campaigns and even identification of market trending. Multiple existing
Publikováno v:
Revista Brasileira de Computação Aplicada, Vol 12, Iss 1, Pp 16-31 (2020)
Este trabalho realiza a caracterização e análise dos dados de séries temporais de cotações históricas de 9 ativos(i.e., BBAS3, PETR4, JBSS3, KROT3, LAME4, MRVE4, NATU3, RADL3 e TIMP3) de segmentos distintos do índiceBovespa (Ibovespa) com a p
Publikováno v:
WebMedia
Recommendation Systems have concerned about the online environment of real-world scenarios where the system should continually learn and predict new recommendations. Current works have handled it as a Multi-Armed Bandit (MAB) problem by proposing par
Publikováno v:
Information Systems. 80:1-12
The success of Web-based applications depends on their ability to convert first-time users into recurring ones. This problem is known as Pure Cold-Start and it refers to the capability of Recommender Systems (RSs) providing useful recommendations to
Publikováno v:
SSCI
Forecasting asset volatility is a common and important application in finance, often used as a measure of the future risk of an investment. With high-frequency data availability in the last few decades, new volatility models have been proposed that m
Autor:
Heitor Werneck, Nícollas Silva, Matheus Carvalho Viana, Leonardo Rocha, Adriano C. M. Pereira, Fernando Mourão
Publikováno v:
WebMedia
The popularization of Location-based social networks (LBSNs) in last years has provided a lot of improvements in several Recommender Systems to the task of points-of-interest (POI) recommendation. In this paper, we provide an updated view of the POI
Publikováno v:
WebMedia
Location-Based Social Networks (LBSNs) have become important tools for people interested in exploring new places. And, similar to traditional recommendation domains, handling the trade-off between accuracy and diversity is a major challenge to provid