Multi-SPMiner: A Deep Learning Framework for Multi-Graph Frequent Pattern Mining with Application to spatiotemporal Graphs
Authors:
- Assaad ZeghinaAZAssaad Zeghina
- Aurélie LeborgneALAurélie Leborgne
- Florence Le BerFBFlorence Le Ber
- Antoine VacavantAVAntoine Vacavant
Open Access
- 8 December 2023
- journal article
- research article
- Published by Elsevier in Procedia Computer Science
- Vol. 225, 1094-1103
Abstract
No abstract availableKeywords
Funding Information
- ANR
This publication has 11 references indexed in Scilit:
- Deep Learning on Graphs: A SurveyIEEE Transactions on Knowledge and Data Engineering, 2020
- Mining frequent subgraphs in multigraphsInformation Sciences, 2018
- HINMINE: heterogeneous information network mining with information retrieval heuristicsJournal of Intelligent Information Systems, 2017
- A survey of heterogeneous information network analysisIEEE Transactions on Knowledge and Data Engineering, 2016
- Applications of Frequent Pattern Mining2014
- GraMiProceedings of the VLDB Endowment, 2014
- Modeling consistency of spatio-temporal graphsData & Knowledge Engineering, 2013
- A survey of frequent subgraph mining algorithmsThe Knowledge Engineering Review, 2012
- Finding Frequent Patterns in a Large Sparse Graph*Data Mining and Knowledge Discovery, 2005
- Qualitative Spatial Representation and Reasoning with the Region Connection CalculusGeoInformatica, 1997