Agent mining approaches: an ontological view

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.

Special issue on ontologies and standards for intelligent systems: editorial

“…In the second article of this special issue ('Agent mining approaches: An ontological view'), Grislin-Le Strugeon et al (2021) analyses ontologies for agent systems and formalizes both agent's knowledge and data mining domain to provide the ontological representation of the agent mining domain according to the addressed problems, the application domains, the agent-related and mining-related elements, the models, processes, and algorithms. Since ontologies offer the capability to express semantics and constraints from the concepts, the shared knowledge obtained about the agent mining approaches could be specified and represented explicitly, resulting in the design of communication and coordination elements for the agents to share their common environment made of common resources.…”