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Publications

Publications by João Gama

2019

Contrasting logical sequences in multi-relational learning

Authors
Ferreira, CA; Gama, J; Costa, VS;

Publication
PROGRESS IN ARTIFICIAL INTELLIGENCE

Abstract
In this paper, we present the BeamSouL sequence miner that finds sequences of logical atoms. This algorithm uses a levelwise hybrid search strategy to find a subset of contrasting logical sequences available in a SeqLog database. The hybrid search strategy runs an exhaustive search, in the first phase, followed by a beam search strategy. In the beam search phase, the algorithm uses the confidence metric to select the top k sequential patterns that will be specialized in the next level. Moreover, we develop a first-order logic classification framework that uses predicate invention technique to include the BeamSouL findings in the learning process. We evaluate the performance of our proposals using four multi-relational databases. The results are promising, and the BeamSouL algorithm can be more than one order of magnitude faster than the baseline and can find long and highly discriminative contrasting sequences.

2019

Improving Portfolio Optimization Using Weighted Link Prediction in Dynamic Stock Networks

Authors
Castilho, D; Gama, J; Mundim, LR; de Carvalho, ACPLF;

Publication
COMPUTATIONAL SCIENCE - ICCS 2019, PT III

Abstract
Portfolio optimization in stock markets has been investigated by many researchers. It looks for a subset of assets able to maintain a good trade-off control between risk and return. Several algorithms have been proposed to portfolio management. These algorithms use known return and correlation data to build subset of recommended assets. Dynamic stock correlation networks, whose vertices represent stocks and edges represent the correlation between them, can also be used as input by these algorithms. This study proposes the definition of constants of the classical mean-variance analysis using machine learning and weighted link prediction in stock networks (method named as MLink). To assess the performance of MLink, experiments were performed using real data from the Brazilian Stock Exchange. In these experiments, MLink was compared with mean-variance analysis (MVA), a popular method to portfolio optimization. According to the experimental results, using weighted link prediction in stock networks as input considerably increases the performance in portfolio optimization task, resulting in a gross capital increase of 41% in 84 days.

2018

Message from the program chairs

Authors
Washio, T; Gama, J; Li, Y; Parekh, R; Liu, H; Bifet, A; De Veaux, RD;

Publication
Proceedings - 2017 International Conference on Data Science and Advanced Analytics, DSAA 2017

Abstract

2013

Preface

Authors
Gama, J; May, M; Marques, N; Cortez, P; Ferreira, CA;

Publication
CEUR Workshop Proceedings

Abstract

2017

Preface

Authors
Oliveira, E; Cardoso, HL; Gama, J; Vale, Z;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract

2018

Preface

Authors
Gama, J;

Publication
MATEC Web of Conferences

Abstract

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