A systematic mapping study on agent mining

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2021-01-11 DOI:10.1080/0952813X.2020.1864784
E. L. Strugeon, K. Oliveira, Marie Thilliez, Dorian Petit
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引用次数: 3

Abstract

ABSTRACT 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.
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智能体挖掘的系统映射研究
在过去的二十年中,在结合智能体能力(知识处理、通信、学习、移动性等)和数据挖掘方法(聚类、决策树、本体等)的应用领域发表了许多研究。我们进行了系统的映射研究,以定量分析这些对代理挖掘的贡献。我们确定大多数出版物都是在使用代理系统收集或挖掘数据的数据挖掘领域。一些使用数据挖掘解决方案来改进代理行为,很少有出版物将代理和挖掘方法结合在一起。在后一种情况下,大多数是在最近几年发表的,其中突出了综合药剂和挖掘方法的研究进展。
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来源期刊
CiteScore
6.10
自引率
4.50%
发文量
89
审稿时长
>12 weeks
期刊介绍: Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving
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