The NOESIS Network-Oriented Exploration, Simulation, and Induction System

TL;DR

NOESIS is an open source framework that offers comprehensive network data mining tools, including analysis, visualization, and prediction techniques, with a user-friendly interface and modular design for easy integration.

Contribution

It introduces a versatile, lightweight, and modular network data mining framework with a graphical interface, supporting a wide range of analysis and visualization methods.

Findings

Provides a comprehensive set of network analysis tools

Features a user-friendly graphical interface

Designed with modular and parallel programming principles

Abstract

Network data mining has become an important area of study due to the large number of problems it can be applied to. This paper presents NOESIS, an open source framework for network data mining that provides a large collection of network analysis techniques, including the analysis of network structural properties, community detection methods, link scoring, and link prediction, as well as network visualization algorithms. It also features a complete stand-alone graphical user interface that facilitates the use of all these techniques. The NOESIS framework has been designed using solid object-oriented design principles and structured parallel programming. As a lightweight library with minimal external dependencies and a permissive software license, NOESIS can be incorporated into other software projects. Released under a BSD license, it is available from http://noesis.ikor.org.