Performs context based spelling correction.

Based on: https://arxiv.org/pdf/1910.11242.pdf

work in progress. NOT yet production ready

See the most important environment variables in order to get started.

SC_ADDR: The address the server listens to (default :10000)
SC_SENTENCES_PATH: The path of the file containing sentences from the language
                    you want to perform spelling correction for. (File must be gzipped)
SC_DICT_PATH: The path of the file  with word frequency dictionary for the languate. (file must be gzipped)

See the internal/config/config.go for additional variables

Example assuming that the train files are in the datasets/ folder.

1. make build
2. SC_ADDR=:10000 SC_SENTENCES_PATH=datasets/sentences.txt2.gz SC_DICT_PATH=datasets/de-100k.txt.gz ./spell-correct-server

It starts a web server listening by default on port 10.000

curl  GET 'http://localhost:10000?query=piza%20in%20bonn'

It gives you back the suggestions. The suggestions are ordered with the ones the algorithm decides are most relevant first.

Example:

1. make docker-build
2. docker run -p 10000:10000 -v /home/giorgos/datasets:/datasets -e SC_SENTENCES_PATH=/datasets/sentences.txt2 -e SC_DICT_PATH=/datasets/de-100k.txt spell-correctort

• https://github.com/Oikopedo

• https://arxiv.org/pdf/1910.11242.pdf

• https://github.com/wolfgarbe/SymSpell

• https://github.com/eskriett/spell

• https://github.com/json-iterator/go

• https://github.com/qiangxue/go-env