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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.
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented.
Project files contain:
- simple code to hold/read/write data and perform sample processing.
- BioC-formatted corpora
- BioC tools that work with BioC corpora
BioC goals
- simplicity
- interoperability
- broad use
- reuse
There should be little investment required to learn to use a format or a software module to process that format. We are...
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.
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