Cookies
O website necessita de alguns cookies e outros recursos semelhantes para funcionar. Caso o permita, o INESC TEC irá utilizar cookies para recolher dados sobre as suas visitas, contribuindo, assim, para estatísticas agregadas que permitem melhorar o nosso serviço. Ver mais
Aceitar Rejeitar
  • Menu
Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Bruno Miguel Veloso
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    01 março 2013
003
Publicações

2022

Stream-based explainable recommendations via blockchain profiling

Autores
Leal, F; Veloso, B; Malheiro, B; Burguillo, JC; Chis, AE; Gonzalez Velez, H;

Publicação
INTEGRATED COMPUTER-AIDED ENGINEERING

Abstract
Explainable recommendations enable users to understand why certain items are suggested and, ultimately, nurture system transparency, trustworthiness, and confidence. Large crowdsourcing recommendation systems ought to crucially promote authenticity and transparency of recommendations. To address such challenge, this paper proposes the use of stream-based explainable recommendations via blockchain profiling. Our contribution relies on chained historical data to improve the quality and transparency of online collaborative recommendation filters - Memory-based and Model-based - using, as use cases, data streamed from two large tourism crowdsourcing platforms, namely Expedia and TripAdvisor. Building historical trust-based models of raters, our method is implemented as an external module and integrated with the collaborative filter through a post-recommendation component. The inter-user trust profiling history, traceability and authenticity are ensured by blockchain, since these profiles are stored as a smart contract in a private Ethereum network. Our empirical evaluation with HotelExpedia and Tripadvisor has consistently shown the positive impact of blockchain-based profiling on the quality (measured as recall) and transparency (determined via explanations) of recommendations.

2022

The Importance of Digital Transformation in International Business

Autores
Pereira, CS; Durao, N; Moreira, F; Veloso, B;

Publicação
SUSTAINABILITY

Abstract
This study was developed under the scope of a Portuguese project focused on the entrepreneur’s perspective and perception on the internationalization process of his company: more specifically, about the factors that enhanced the company entry into foreign markets as well as the constraints found in this process. This work focuses on the importance of using digital transformation to integrate technological tools in international business practice and strategy and the obstacles encountered with introducing these new technologies. This study aims to determine the relationships between technology categories and obstacles. The final goal is to assess the impact of these characteristics of the companies by the sector of economic activity, size, and percentage of profits resulting from international expansion. A questionnaire was designed and sent by email to 8183 companies from the AICEP database, distributed by three main activity sectors. A total of 310 valid answers were gathered from the Portuguese internationalized companies. The research limitations are related to the reduced number of interviews. These interviews showed that managers were not aware of the concept of digital transformation and misunderstood the use of digital technologies in the internationalization process of the business. This limitation can add some bias to the qualitative results. In addition to these limitations, the number of responses per sector was also not homogeneous. The practical implications of this study are that managers and top-level executives can use that to better understand how companies could use digital tools and what obstacles they should avoid when they want to internationalize their business. This paper is one of the first research contributions to analyze the impact of digital transformation in the internalization of Portuguese companies.

2022

ZeroBERTo: Leveraging Zero-Shot Text Classification by Topic Modeling

Autores
Alcoforado, A; Ferraz, TP; Gerber, R; Bustos, E; Oliveira, AS; Veloso, BM; Siqueira, FL; Costa, AHR;

Publicação
COMPUTATIONAL PROCESSING OF THE PORTUGUESE LANGUAGE, PROPOR 2022

Abstract

2022

A Fault Detection Framework Based on LSTM Autoencoder: A Case Study for Volvo Bus Data Set

Autores
Davari, N; Pashami, S; Veloso, B; Fan, YT; Pereira, PM; Ribeiro, RP; Gama, J; Nowaczyk, S;

Publicação
ADVANCES IN INTELLIGENT DATA ANALYSIS XX, IDA 2022

Abstract

2022

Personalised Combination of Multi-Source Data for User Profiling

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

Publicação
Lecture Notes in Networks and Systems

Abstract