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This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format.
It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts.
https://aseryla2.sourceforge.io/
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project.
Pretty Damn Quick (PDQ) analytically solves queueing network models of computer and manufacturing systems, data networks, etc., written in conventional programming languages. Generic or customized reports of predicted performance measures are output.
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This is a implementation of the 'enhanced Topic-based Vector Space Model' (eTVSM) using the python language. A Java-Version and maybe other java-code contributions are planned.