A Multi-Agent Architecture for Data Analysis

Gianfranco Lombardo, Paolo Fornacciari, Monica Mordonini, Michele Tomaiuolo and Agostino Poggi
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Gianfranco Lombardo: Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Paolo Fornacciari: Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Monica Mordonini: Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Michele Tomaiuolo: Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Agostino Poggi: Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy

Future Internet, 2019, vol. 11, issue 2, 1-12

Abstract: ActoDatA (Actor Data Analysis) is an actor-based software library for the development of distributed data mining applications. It provides a multi-agent architecture with a set of predefined and configurable agents performing the typical tasks of data mining applications. In particular, its architecture can manage different users’ applications; it maintains a high level of execution quality by distributing the agents of the applications on a dynamic set of computational nodes. Moreover, it provides reports about the analysis results and the collected data, which can be accessed through either a web browser or a dedicated mobile APP. After an introduction about the actor model and the software framework used for implementing the software library, this article underlines the main features of ActoDatA and presents its experimentation in some well-known data analysis domains.

Keywords: social media analysis; data mining; multi-agent architecture; actor model; Java (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2019
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