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.

中文翻译：

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代理挖掘方法：本体论观点

作为一个结合多智能体系统、数据挖掘和知识发现的跨学科领域，智能体挖掘目前正在实践中。开发代理挖掘应用程序涉及软件代理和数据挖掘 (DM) 领域的不同方法（模型、架构、技术等）的组合。本文通过深入分析来自系统文献综述的 121 篇论文，对代理挖掘系统中使用的方法进行了调查。定义了一个本体来利用从这项研究中收集的知识。本体根据七个主要方面进行组织：解决的问题、应用领域、代理相关和挖掘相关的元素、模型、流程和算法。该本体旨在为有关代理挖掘应用程序设计的决策提供支持。