Cookies
Usamos cookies para melhorar nosso site e a sua experiência. Ao continuar a navegar no site, você aceita a nossa política de cookies. Ver mais
Fechar
  • Menu
Sobre
Download foto HD

Sobre

Benedita Malheiro holds a PhD. and a MSc. in Electrical Engineering and Computers and a five year graduation degree in Electrical Engineering from the University of Porto (Faculty of Engineering). She is an Adjunct Professor at the Electrical Engineering Department of the Instituto Superior de Engenharia do Porto (ISEP) where she is responsible for two modules of the MSc. in Electrical and Computers Engineering degree and supervises undergraduate (Final Project/Internship) and postgraduate (Thesis/Dissertation) students. As a researcher she is specialized in problems of a distributed, dynamic and decentralized nature.

Tópicos
de interesse
Detalhes

Detalhes

002
Publicações

2019

Analysis and prediction of hotel ratings from crowdsourced data

Autores
Leal, F; Malheiro, B; Burguillo, JC;

Publicação
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

Abstract
Crowdsourcing has become an essential source of information for tourism stakeholders. Every day, tourists leave large volumes of feedback data in the form of posts, likes, textual reviews, and ratings in dedicated crowdsourcing platforms. This behavior makes the analysis of crowdsourced information strategic, allowing the discovery of important knowledge regarding tourists and tourism resources. This paper presents a survey on the analysis and prediction of hotel ratings from crowdsourced data, covering both off-line (batch) and on-line (stream-based) processing. Specifically, it reports multiple rating-based profiling, recommendation, and evaluation techniques. While most of the surveyed works adopt entity-based multicriteria profiling, prerecommendation filtering, and off-line processing, the latest hotel rating prediction trends include feature-based, trust and reputation modeling, postrecommendation filtering, and on-line processing. Additionally, since the volume of crowdsourced ratings tends to increase, the deployment of profiling and recommendation algorithms on high-performance computing resources should be further explored. This article is categorized under: Application Areas > Internet and Web-Based Applications. © 2018 Wiley Periodicals, Inc.

2019

On-line guest profiling and hotel recommendation

Autores
Veloso, BM; Leal, F; Malheiro, B; Carlos Burguillo, JC;

Publicação
Electronic Commerce Research and Applications

Abstract

2019

Scalable Modelling and Recommendation using Wiki-based Crowdsourced Repositories

Autores
Leal, F; Veloso, BM; Malheiro, B; Gonzalez Velez, H; Carlos Burguillo, JC;

Publicação
Electronic Commerce Research and Applications

Abstract

2019

Vertical Farming—An EPS@ISEP 2018 Project

Autores
Sevastiadou, A; Luts, A; Pretot, A; Trendafiloski, M; Basurto, R; Blaszczyk, S; Malheiro, B; Ribeiro, C; Justo, J; Silva, MF; Ferreira, P; Guedes, P;

Publicação
Linear and Nonlinear Programming - International Series in Operations Research & Management Science

Abstract

2019

Water Intellibuoy—An EPS@ISEP 2018 Project

Autores
Colen, ME; Houard, H; Imenkamp, C; van Velthoven, G; Pajula, S; Malheiro, B; Ribeiro, C; Justo, J; Silva, MF; Ferreira, P; Guedes, P;

Publicação
Linear and Nonlinear Programming - International Series in Operations Research & Management Science

Abstract

Teses
supervisionadas

2018

O Impacto da Automatização e Inteligência Artificial nos Serviços Partilhados

Autor
João Francisco de Magalhães e Silva

Instituição
UP-FEUP

2017

Media Content Personalisation Brokerage Platform

Autor
Bruno Miguel Delindro Veloso

Instituição
Outra

2016

Plataforma de Competição de Veleiros Autónomos

Autor
BRUNO MIGUEL FERREIRA ALVES

Instituição
IPP-ISEP

2016

Renegociação de Contratos de Intermediação da Comercialização Eletrónica de Recursos de Cloud Computing

Autor
RÚBEN DE CASTRO RODRIGUES MOREIRA DA CUNHA

Instituição
IPP-ISEP

2016

Automatic Fluid Sampler

Autor
PEPIJN DE WINTER

Instituição
IPP-ISEP