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Authors: Víctor Martínez ; Fernando Berzal and Juan-Carlos Cubero

Affiliation: University of Granada, Spain

ISBN: 978-989-758-158-8

Keyword(s): Network Analysis, Network Visualization, Community Detection, Structural Properties.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Data Analytics ; Data Engineering ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Software Development ; Structured Data Analysis and Statistical Methods ; Symbolic Systems

Abstract: NOESIS is a software framework for the development of data mining techniques for networked data. As an open source project, released under a BSD license, NOESIS intends to provide the necessary infrastructure for solving complex network data mining problems. Currently, it includes a large collection of popular network-related data mining techniques, including the analysis of network structural properties, community detection algorithms, link scoring and prediction methods, and network visualization techniques. The design of NOESIS tries to facilitate the development of parallel algorithms using solid object-oriented design principles and structured parallel programming. NOESIS can be used as a stand-alone application, as many other network analysis packages, and can be included, as a lightweight library, in domain-specific data mining applications and systems.

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Paper citation in several formats:
Martínez V., Berzal F. and Cubero J. (2015). The NOESIS Open Source Framework for Network Data Mining.In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 316-321. DOI: 10.5220/0005610103160321

@conference{kdir15,
author={Víctor Martínez and Fernando Berzal and Juan-Carlos Cubero},
title={The NOESIS Open Source Framework for Network Data Mining},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={316-321},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005610103160321},
isbn={978-989-758-158-8},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - The NOESIS Open Source Framework for Network Data Mining
SN - 978-989-758-158-8
AU - Martínez V.
AU - Berzal F.
AU - Cubero J.
PY - 2015
SP - 316
EP - 321
DO - 10.5220/0005610103160321

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