This project was completed during the Lviv Data Science Summer School 2016. The project supervisor – Jordi Carrera Ventura.
The project goal was to create a state-of-the-art automatic spellchecking system using the most recent advances in the industry (word embeddings, automatic word sense disambiguation through neural nets) as well as traditional technologies (collocation extraction, n-gram models, shallow syntactic parsing). The system should be capable of using linguistic information and semantic context both to correct mistakes and to improve users’ word choice by suggesting better keywords whenever less specific ones are being used.
If you are interested in more details, please contact firstname.lastname@example.org