The NOESIS Network-Oriented Exploration, Simulation, and Induction System
It offers a lightweight, permissively licensed tool for researchers and practitioners working with network data, but it is incremental as it packages existing methods rather than introducing new ones.
The paper introduces NOESIS, an open-source framework for network data mining that provides a collection of techniques for analysis, community detection, link prediction, and visualization, along with a graphical user interface, designed with object-oriented and parallel programming principles.
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.