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GCKit

(G)raph (C)lustering Kit, A project to reach optimal clusterization and classification solution.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. For any commercial use, please contact the author 'Zelakolase[at]tuta.io' to get a written permission if needed.

Description & Problem Statement

GCKit is a research project to find optimal clusterization and classification algorithm(s). Classification and Clusterization techniques are particularly used in the analysis of Protein-Protein interaction networks, and it is a very active field of research. The project aims to do the following:

  1. Establish proper grading and indicators for the performance and correctness of any classification algorithm
  2. Find an optimal algorithm for classification and clusterization highly-connected graphs.

Besides, GCKit has Power Set calculation method, to get significant clusters via bruteforce over the whole graph.

NOTE: This kit is assumes that every input graph is a weighted graph.

Table of contents:

General Technical Information

We used Java programming language to build the kit, with SparkDB. All of the source code files will be included inside 'Application/' The source code tries to follow ISO-25010 standard for code quality, to ensure high readability and maintainability.

Applications in Kit

Name Function
Cyclops Proposed Clusterization algorithm for weighted directed graphs
Harmonia Evaluation of the correctness and performance for any clusterization process

Check the README of each application for more information about these applications. All of the source code exists in 'Application/'

Build and run

All of the commands must be executed in 'Application/src/'

  • Build classfile: $ javac App.java
  • Run classfile: $ java app

What is the next step?

Go to Application/README.md for more information about the code

Author Information

Morad A., E-mail: Zelakolase[at]tuta.io, website: zelakolase.neocities.org

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(G)raph (C)lustering Kit, A project to reach the optimal clustering algorithm

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