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Publicações

Publicações por LIAAD

2018

cf2vec: Collaborative Filtering algorithm selection using graph distributed representations

Autores
Cunha, T; Soares, C; de Carvalho, ACPLF;

Publicação
CoRR

Abstract

2018

Towards Reproducible Empirical Research in Meta-Learning

Autores
Rivolli, A; Garcia, LPF; Soares, C; Vanschoren, J; de Carvalho, ACPLF;

Publicação
CoRR

Abstract

2018

Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets

Autores
Cunha, T; Soares, C; de Carvalho, ACPLF;

Publicação
CoRR

Abstract

2018

Building robust prediction models for defective sensor data using Artificial Neural Networks

Autores
Shekar, AK; de Sá, CR; Ferreira, H; Soares, C;

Publicação
CoRR

Abstract

2018

Smart energy management as a means towards improved energy efficiency

Autores
Lindert, Dt; de Sá, CR; Soares, C; Knobbe, AJ;

Publicação
CoRR

Abstract

2018

Personalised Dynamic Viewer Profiling for Streamed Data

Autores
Veloso, B; Malheiro, B; Burguillo, JC; Foss, JD; Gama, J;

Publicação
WorldCIST (2)

Abstract
Nowadays, not only the number of multimedia resources available is increasing exponentially, but also the crowd-sourced feedback volunteered by viewers generates huge volumes of ratings, likes, shares and posts/reviews. Since the data size involved surpasses human filtering and searching capabilities, there is the need to create and maintain the profiles of viewers and resources to develop recommendation systems to match viewers with resources. In this paper, we propose a personalised viewer profiling technique which creates individual viewer models dynamically. This technique is based on a novel incremental learning algorithm designed for stream data. The results show that our approach outperforms previous approaches, reducing substantially the prediction errors and, thus, increasing the accuracy of the recommendations.

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