NOESIS: A Framework for Complex Network Data Analysis. (31st October 2019)

• Record Type: Journal Article
• Authors: Martínez, Víctor; Berzal, Fernando; Cubero, Juan-Carlos
• Other Names: Cimini Giulio Academic Editor.
• Is Part Of: Complexity. Volume 2019(2019)
• Publication Date: 2019-10-31
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2019/1439415
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Network data mining has attracted a lot of attention since a large number of real-world problems have to deal with complex network data. In this paper, we present NOESIS, an open-source framework for network-based data mining. NOESIS features a large number of techniques and methods for the analysis of structural network properties, network visualization, community detection, link scoring, and link prediction. The proposed framework has been designed following solid design principles and exploits parallel computing using structured parallel programming. NOESIS also provides a stand-alone graphical user interface allowing the use of advanced software analysis techniques to users without prior programming experience. This framework is available under a BSD open-source software license.