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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/
Predicting Organic Reactions using Neural Networks.
The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule.
Beam search is used in Version 2, to generate top 5 predictions.
Maximum input length for the model is 15 (excluding spaces).