Graph Pattern Mining Paradigms: Consolidation and Renewed Bearing

Dias, Vinicius; Ferraz, Samuel; Vadlamani, Aditya; Erfanian, Mahdi; Teixeira, Carlos H. C.; Guedes, Dorgival; Meira, Wagner; Parthasarathy, Srinivasan

doi:10.1109/hipc58850.2023.00040

2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC) 2023

DOI: 10.1109/hipc58850.2023.00040

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Graph Pattern Mining Paradigms: Consolidation and Renewed Bearing

Vinicius Dias,

Samuel Ferraz,

Aditya Vadlamani

et al.

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2024

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Cited by 1 publication

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Graph Pattern Mining: consolidating models, systems, and abstractions

Dias,

Guedes

2024

Anais Estendidos Do XXXIX Simpósio Brasileiro De Banco De Dados (SBBD Estendido 2024)

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This text summarizes the key contributions of the dissertation entitled "Graph Pattern Mining: consolidating models, systems, and abstractions", approved in the Graduate Program in Computer Science of the Federal University of Minas Gerais (DCC/UFMG) Graph Pattern Mining (GPM) refers to a class of problems involving the processing of subgraphs extracted from larger graphs. Applications to GPM algorithms include querying subgraphs with given properties of interest, identifying motif structures in biological networks, among others. GPM algorithms are challenging to develop and thus, general-purpose GPM systems emerge as a solution to improve the user experience with such algorithms. In this dissertation we propose a primitive-based model for representing GPM algorithms, a distributed system implementing this model, and an extensive experimental study of popular algorithms used in GPM systems. We demonstrate empirically the effectiveness of our model by showing competitive performance without sacrificing the expressiveness of algorithms.

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Graph Pattern Mining: consolidating models, systems, and abstractions

Dias,

Guedes

2024

Anais Estendidos Do XXXIX Simpósio Brasileiro De Banco De Dados (SBBD Estendido 2024)

View full text Add to dashboard Cite

show abstract

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Graph Pattern Mining Paradigms: Consolidation and Renewed Bearing

Cited by 1 publication

References 42 publications

Graph Pattern Mining: consolidating models, systems, and abstractions

Graph Pattern Mining: consolidating models, systems, and abstractions

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