2021
Authors
Barbosa, A; Ribeiro, P; Dutra, I;
Publication
Machine Learning and Data Mining for Sports Analytics - 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected Papers
Abstract
Association football has been the subject of many research studies. In this work we present a study on player similarity using passing sequences extracted from games from the top-5 European football leagues during the 2017/2018 season. We present two different approaches: first, we only count the motifs a player is involved in; then we also take into consideration the specific position a player occupies in each motif. We also present a new way to objectively judge the quality of the generated models in football analytics. Our results show that the study of passing sequences can be used to study player similarity with relative success. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
2021
Authors
Eddin, AN; Bono, J; Aparício, D; Polido, D; Ascensão, JT; Bizarro, P; Ribeiro, P;
Publication
CoRR
Abstract
2021
Authors
Rocha, R; Formisano, A; Liu, YA; Areias, M; Angelopoulos, N; Bogaerts, B; Dodaro, C; Alviano, M; Brik, A; Vennekens, J; Pozzato, GL; Zhou, NF; Dahl, V; Fodor, P;
Publication
Electronic Proceedings in Theoretical Computer Science, EPTCS
Abstract
2021
Authors
Areias, M; Rocha, R;
Publication
Proceedings - 2021 20th International Symposium on Parallel and Distributed Computing, ISPDC 2021
Abstract
A key aspect of any hash map design is the problem of dynamically resizing it in order to deal with hash collisions. In this context, elasticity refers to the ability to automatically resize the internal data structures that support the hash map operations in order to meet varying workloads, thus optimizing the overall memory consumption of the hash map. This work extends a previous lock-free hash trie design to support elastic hashing, i.e., expand saturated hash levels and compress unused hash levels, such that, at each point in time, the number of levels in a path matches the current demand as closely as possible. Experimental results show that elasticity effectively improves the search operation and, in doing so, our design becomes very competitive when compared to other state-of-the-art designs implemented in Java. © 2021 IEEE.
2021
Authors
Queirós, R; Pinto, M; Simões, A; Portela, F; Pereira, MJ;
Publication
SLATE
Abstract
2021
Authors
Simões, A; Queirós, R;
Publication
Second International Computer Programming Education Conference, ICPEC 2021, May 27-28, 2021, University of Minho, Braga, Portugal.
Abstract
This article documents some experiments on teaching a class on a Master Degree Program using a different perspective on gamification. Instead of winning badges or getting achievements, students earn classification points. This allows them to work as hard as they are willing, having in mind their current classification and how far they can reach. In the specific experiment being reported, students can earn final grade points with pull requests to a shared class project. The article describes the details of the experiment, extrapolates on different ideas for implementing this in other classes, and concludes with the pros and cons of such approach for student evaluation. © Alberto Simões and Ricardo Queirós; licensed under Creative Commons License CC-BY 4.0 Second International Computer Programming Education Conference (ICPEC 2021).
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