AIBench A free framework for fast application development
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AIBench Description

A free framework for fast application development AIBench (Artificial Intelligence workBENCH) is a free and open source, lightweight, non-intrusive, MVC-based Java application framework intended to fast develop desktop-based applications, specially focused in the scientific domain.AIBench was created inside the SING research group focused in the IA/data-mining field, where several applications has been developed through the last years solving real and practical problems. However, these applications were isolated between them, with a marginal reuse of code and with a hard integration work.In the IA field, and more specially, in the data-mining applications we always perform these types of operations:· Data loading, from some format/origin (text files, XML, databases, etc.).· Data-type design and definition in the programming language to support the in-memory representation of the problem-related data.· Perform analysis of the data (neural networks, fuzzy systems, genetic algorithms, etc.).· Data saving, to some format/destination (text files, XML, databases, etc.).When a real problem were targeted by our group, a new application development were started (often from scratch), taking chunks of code (if possible) from past applications and also developing newer chunks of code to finally obtain a new hard-coded, problem-centric application.If you are thinking that AIBench is a(nother) data-mining toolkit, such Weka or the recent Java Data Mining API (JSR-73), you are wrong, let us explain.The basic difference between our hard-coded applications was the different combination of these chunks of code. For example, sometimes a neural network was applied to two different problems, where the data origin was the unique difference, so we only needed to replace the load operation with a new one. Keeping this idea in mind, we found essential that the combination itself must be isolated from the operations. Here is where AIBench comes as a new framework to develop these kinds of applications.To achieve this isolation it was necessary to define an operation model, that is, how these chunks of code (and the new ones) should be programmed in order to achive the transparent combination and code reuse. If the operations are well defined (well defined INPUT/OUTPUT), we could achieve that isolation and more benefits that are explained in the next sections. Requirements: · Java What's New in This Release: · Added support for enabling/disabling operations via Core API calls · Toolbar support. See http://www.aibench.org/wiki/index.php/Toolbar · New plugin management/update plugin (now testing). See http://www.aibench.org/wiki/index.php/Plugin_Management_(Now_testing) · New native Help support. See http://www.aibench.org/wiki/index.php/Help · New Documentor plugin to generate technical reports of any AIBench application · Some bug fixes.

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