Search Results for "delphi database framework"
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Showing 9 open source projects for "delphi database framework"
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S-Match
S-Match is a semantic matching framework.
S-Match is a semantic matching framework. S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another. S-Match contains implementations of the semantic matching, minimal semantic matching and structure preserving semantic matching algorithms. -
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Weka4OC GUI for Overlapping clustering
Weka4OC: Weka for Overlapping Clustering is a GUI extending WEKA
This is a GUI application for learning non disjoint groups based on Weka machine learning framework. It offers a variety of learning methods, based on k-means, able to produce overlapping clusters. The application also contains an evaluation framework that calculates several external validation measures. The application offers a visualization tool to discover overlapping groups. -
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Beagle is Java open source framework for running and managing nondeterministic algorithms such as genetic algorithms for solving complex problems. Beagle is fully modular and maintains whole history of algorithm progress for further analysis.
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The Open Optimization for Java provides a framework and the implementation of commonly-used algorithms found in Graph Theory and Network Optimization, e.g. shortest path and postman problem.
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a framework library with a template method interface and inheritable classes for an executable process design which produces an executable which is both a GUI and a console application. It provides multi-threading for work items of the provider process .
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The Catalsyt Framework is a refinement on the MVC framework. It provides greater focus on user business workflow rather than application workflow. It's goal is to enable business analysis and developers to work closer.
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MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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