Authors:
Víctor Martínez
;
Fernando Berzal
and
Juan-Carlos Cubero
Affiliation:
University of Granada, Spain
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.