TELKOMNIKA Telecommunication, Computing, Electronics and Control
Spatial association discovery process using frequent subgraph mining
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Spatial association discovery process using frequent subgraph mining
Spatial association discovery process using frequent subgraph mining
Subject
Frequent subgraph mining, SARM, Spatial association mining, Spatial data mining, Spatial knowledge discovery
Description
Spatial associations are one of the most relevant kinds of patterns used by business intelligence regarding spatial data. Due to the characteristics of this particular type of information, different approaches have been proposed for spatial association mining. This wide variety of methods has entailed the need for a process to integrate the activities for association discovery, one that is easy to implement and flexible enough to be adapted to any particular situation, particularly for small and medium-size projects to guide the useful pattern discovery process. Thus, this work proposes an adaptable knowledge discovery process that uses graph theory to model different spatial relationships from multiple scenarios, and frequent subgraph mining to discover spatial associations. A proof of concept is presented using real data.
Creator
Giovanni Daian Rottoli, Hernan Merlino
Source
DOI: 10.12928/TELKOMNIKA.v18i4.13858
Publisher
Universitas Ahmad Dahlan
Date
August 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Giovanni Daian Rottoli, Hernan Merlino, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Spatial association discovery process using frequent subgraph mining,” Repository Horizon University Indonesia, accessed November 22, 2024, https://repository.horizon.ac.id/items/show/3934.
Spatial association discovery process using frequent subgraph mining,” Repository Horizon University Indonesia, accessed November 22, 2024, https://repository.horizon.ac.id/items/show/3934.