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
Aceitar Rejeitar
  • Menu
Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Bruno Miguel Veloso
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    01 março 2013
002
Publicações

2021

Classification and Recommendation With Data Streams

Autores
Veloso, B; Gama, J; Malheiro, B;

Publicação
Encyclopedia of Information Science and Technology, Fifth Edition - Advances in Information Quality and Management

Abstract
Nowadays, with the exponential growth of data stream sources (e.g., Internet of Things [IoT], social networks, crowdsourcing platforms, and personal mobile devices), data stream processing has become indispensable for online classification, recommendation, and evaluation. Its main goal is to maintain dynamic models updated, holding the captured patterns, to make accurate predictions. The foundations of data streams algorithms are incremental processing, in order to reduce the computational resources required to process large quantities of data, and relevance model updating. This article addresses data stream knowledge processing, covering classification, recommendation, and evaluation; describing existing algorithms/techniques; and identifying open challenges.

2021

Crowdsourced Data Stream Mining for Tourism Recommendation

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

Publicação
Advances in Intelligent Systems and Computing - Trends and Applications in Information Systems and Technologies

Abstract

2021

Hyperparameter self-tuning for data streams

Autores
Veloso, B; Gama, J; Malheiro, B; Vinagre, J;

Publicação
Information Fusion

Abstract

2021

Improving Student Engagement With Project-Based Learning: A Case Study in Software Engineering

Autores
Morais, P; Ferreira, MJ; Veloso, B;

Publicação
IEEE REVISTA IBEROAMERICANA DE TECNOLOGIAS DEL APRENDIZAJE-IEEE RITA

Abstract
In the area of Information and Communication Technologies, in addition to the problem of engagement, students often have difficulties in learning subjects related to modeling and programming. The reasons for these difficulties are well known and described in the literature, pointing to difficulties in abstraction and logic thinking. Knowing that the value of flexible and personalized learning, teachers are changing the way they teach, using different active learning methodologies, such as flipped classroom, project-based learning, and peer instruction. This paper describes an experiment conducted to improve the learning experiences of the students enrolled in the Computer Science bachelor's degree course, attending three curricular units: Information Systems Development, Data Structures, and Web Languages and Technologies. The approach followed by the teachers used project-based learning as an active learning methodology. This methodology allows us to achieve four main objectives: (i) improve student engagement; (ii) improve learning outcomes achievement (iii) increase the course success rate and (iv) allow students to experience the need for the software development lifecycle, feeling that software engineering is not a block-based process but depending on previous activity, often leads to the need to go back in the process. The results obtained with the use of the active methodology were well accepted by the students and allowed both teachers and students to reach the objectives set.

2020

A 2020 perspective on “Online guest profiling and hotel recommendation”

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

Publicação
Electronic Commerce Research and Applications

Abstract