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Automatic generation of documentation on Delphi projects from source code. Distinctive features are exact parsing gathering lots of information and a division of the parser and configurable generators (HTML, Win- & HTML-Help, PDF, LaTeX, XMI export)
This is a suite of several software agents to provide a complete architecture of lexical base as proposed in Didier Schwab's PhD. thesis. It will be used for automatic translation, information retrieval and other natural language processing tasks.
The Semantic Web Service Composer is a prototyp for semi-automatic data flow design between Semantic Web services described in different domain ontologies. More info: http://citeseer.ist.psu.edu/viewdoc/versions?doi=10.1.1.60.9276
Deploy in 115+ regions with the modern database for every enterprise.
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
A PHP based software for automatic dossier preparation of Wikipedia content. Retrieves Wikipedia content, determines its relevance to a given subject and compiles selected material into a PDF dossier.
FLPD is an automatic learning system based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.
WordFreak is a java-based linguistic annotation tool designed to
support human, and automatic annotation of linguistic data as well as
employ active-learning for human correction of automatically annotated
data.
The TreeQ package is a set of C-language applications that implement a
automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.
JUDGE (Java Utility for Document Genre Eduction) features automatic classification and clustering of documents, optionally as a webservice.
The program is written entirely in Java and makes use of the Weka machine learning toolkit.
OMLT (One More Lousy Translator) is designed to be an interlingual fully automatic machine translation system, capable of taking a source text in one natural language and converting it to any other language for which a module has been written.