scholarly journals Clustering in a Multi-Agent Data Mining Environment

2010 ◽  
pp. 103-114 ◽  
Author(s):  
Santhana Chaimontree ◽  
Katie Atkinson ◽  
Frans Coenen
Keyword(s):  
Data Mining ◽  
Mining Environment ◽  
Multi Agent

Association Rules Algorithms for Data Mining Process Based on Multi Agent System

2020 ◽  
pp. 431-443
Author(s):  
Imane Belabed ◽  
Mohammed Talibi Alaoui ◽  
Jaara El Miloud ◽  
Abdelmajid Belabed
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Agent mining approaches: an ontological view

2021 ◽  
Vol 36 ◽  
Author(s):  
Emmanuelle Grislin-Le Strugeon ◽  
Kathia Marcal de Oliveira ◽  
Dorsaf Zekri ◽  
Marie Thilliez
Keyword(s):  
Data Mining ◽  
Literature Review ◽  
Knowledge Discovery ◽  
Systematic Literature Review ◽  
Software Agent ◽  
Application Domain ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Agent Mining ◽  
Multi Agent

Abstract Introduced as an interdisciplinary area that combines multi-agent systems, data mining and knowledge discovery, agent mining is currently in practice. To develop agent mining applications involves a combination of different approaches (model, architecture, technique and so on) from software agent and data mining (DM) areas. This paper presents an investigation of the approaches used in the agent mining systems by deeply analyzing 121 papers resulting from a systematic literature review. An ontology was defined to capitalize the knowledge collected from this study. The ontology is organized according to seven main facets: the problem addressed, the application domain, the agent-related and the mining-related elements, the models, processes and algorithms. This ontology is aimed at providing support to decisions about agent mining application design.

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