Details
Name
Pedro Manuel RibeiroCluster
Computer ScienceRole
Senior ResearcherSince
03rd May 2010
Nationality
PortugalCentre
Advanced Computing SystemsContacts
+351220402963
pedro.p.ribeiro@inesctec.pt
2022
Authors
Ribeiro, P; Silva, F; Ferreira Mendes, JF; Laureano, RD;
Publication
NetSci-X
Abstract
2022
Authors
Ribeiro, P; Silva, F; Mendes, JF; Laureano, R;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2022
Authors
Silva, VF; Silva, ME; Ribeiro, P; Silva, F;
Publication
DATA MINING AND KNOWLEDGE DISCOVERY
Abstract
2021
Authors
Silva, VF; Silva, ME; Ribeiro, P; Silva, F;
Publication
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
Abstract
2021
Authors
Ribeiro, P; Paredes, P; Silva, MEP; Aparicio, D; Silva, F;
Publication
ACM COMPUTING SURVEYS
Abstract
Computing subgraph frequencies is a fundamental task that lies at the core of several network analysis methodologies, such as network motifs and graphlet-based metrics, which have been widely used to categorize and compare networks from multiple domains. Counting subgraphs is, however, computationally very expensive, and there has been a large body of work on efficient algorithms and strategies to make subgraph counting feasible for larger subgraphs and networks. This survey aims precisely to provide a comprehensive overview of the existing methods for subgraph counting. Our main contribution is a general and structured review of existing algorithms, classifying them on a set of key characteristics, highlighting their main similarities and differences. We identify and describe the main conceptual approaches, giving insight on their advantages and limitations, and we provide pointers to existing implementations. We initially focus on exact sequential algorithms, but we also do a thorough survey on approximate methodologies (with a trade-off between accuracy and execution time) and parallel strategies (that need to deal with an unbalanced search space).
Supervised Thesis
2021
Author
Justino Miguel Ferreira Rodrigues
Institution
UP-FEUP
2021
Author
Maria Alexandra Ramalho de Oliveira
Institution
UP-FEUP
2021
Author
Thiago de Andrade Silva
Institution
UP-FEUP
2021
Author
Ana Micaela Gomes Batista
Institution
UP-FCUP
2020
Author
Henrique Jorge Santos Branquinho
Institution
UP-FCUP
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