A systematic mapping study on agent mining

Over the past two decades, many studies have been published in diverse fields of application combining agent abilities (knowledge processing, communication, learning, mobility, etc.) and data mining approaches (clustering, decision trees, ontologies, etc.). We performed a systematic mapping study to...

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Bibliographic Details
Published inJournal of experimental & theoretical artificial intelligence Vol. 34; no. 2; pp. 189 - 214
Main Authors Grislin-Le Strugeon, Emmanuelle, Marcal de Oliveira, Kathia, Thilliez, Marie, Petit, Dorian
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 04.03.2022
Taylor & Francis Ltd
Subjects
Agent
agent mining
Clustering
Computer Science
Data mining
Decision trees
knowledge discovery
Mapping
systematic mapping study (SMS)
systematic mapping study (SMS)
Agent
knowledge discovery
agent mining
data mining
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Summary:Over the past two decades, many studies have been published in diverse fields of application combining agent abilities (knowledge processing, communication, learning, mobility, etc.) and data mining approaches (clustering, decision trees, ontologies, etc.). We performed a systematic mapping study to quantitatively analyse these contributions about agent mining. We determined that most of the publications were in the field of data mining using agent systems to collect or mine the data. Some used data mining solutions to improve agent behaviour, and very few publications integrated both agent and mining approaches. In the latter case, most were published in the last few years, which highlights the advances in research integrating agents and mining approaches.
ISSN:0952-813X
1362-3079
DOI:10.1080/0952813X.2020.1864784