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The simpliZia-program implements the simplex-algorithm and is designed to help students of Operations Research to understand and learn the algorithm. This is a german project, source and program are actually written in german.
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Project Tokaf is an general implementation of top-k algorithm. It provides interfaces for all modules that are needed. It also features user preferences module, for computing new preferences and manipulating existing ones.
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
The main goal of OWLVE is to visualize graphically any OWL–lite file. Using powerful RCP and GEF technologies will improve the quality of graphics and diagrams.This project includes an algorithm for similarity calculus between two OWL files.
This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.
A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
StrMatch is a simple java program, created for educational purposes, that allows user to test a great part of string matching algorithms.
An intuitive user interface shows each algorithm step accurately...
musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
This project aims to provide developers a convenient library about graph theory algorithm and some basic data structures. It will be developed in Java via Eclipse IDE, supporting both win32 and linux systems, and published as jar files.
distDES is a Java RMI-based application which manages load balancing on heterogeneous clusters. Development will extend the theoretical initial implementation to include clustered Rainbow Table generation and encryption algorithm collision detection.
Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.