Natural Language Processing with ADA 2012

[matteogrella@gmail.com]

Hello,

I'm glad to inform you that at the GitHub links below, you'll find ADA 2012 used for Natural Language Processing and more in general for Artificial Intelligence / Machine Learning.

https://github.com/matteo-grella/mg-research/tree/master/ADADP

ADA Dependency Parser (ADADP).
ADADP is a very basic multilingual statistical dependency parser written in pure ADA that I use to experiment some ideas.  It is based on a shift-reduce transition-based system that produces dependency parse trees for natural language sentences using parsing model learned from annotated corpora.

https://github.com/MGMN/NLPColl/tree/master/DeepParser

NLPColl Deep Parser.
NLPColl Deep Parser is a dependency parser written in Ada 2012 that use Deep Learning / Word Embedding algorithms.  This project derives from Stanford CoreNLP tools (see https://github.com/stanfordnlp/CoreNLP).

https://github.com/MGMN/ada-relax-component-collection/tree/master/src/arcoll/machine_learning

ADA 2012 implementations of Multi-layer Perceptron and Averaged Perceptron.

Best regards,

Matteo Grella
http://www.matteogrella.com