Natural language processing tools for the Dhivehi language.
Project description
dhivehi_nlp
Natural language processing tools for the Dhivehi language.
Demo website to test features: https://dhivehi-nlp.herokuapp.com/
Read the docs: https://dhivehi-nlp.herokuapp.com/docs/index.html
Installation
pip install dhivehi_nlp
Modules
Tokenizer - Tokenize text into separate sentences or words (tokens).
Stopwords - Remove stopwords from text and return the resulting tokens.
Stemmer - Remove suffixes from words to return their root form.
Language Models - Create language models to predict future additions. Language models will give probability based on selected ngram. An ngram is a contiguous sequence of n tokens from the given input text. Use previously built models to predict future words.
Dictionary - Get definitions of Dhivehi words and the word list. Definitions obtained from radheef.mv.
Corpus - Collections of various Dhivehi texts.
Trigram Similarity - Divides words or phrases into sequences of three consecutive letters, placed in a set where the order doesn't matter and duplicates are removed. Used to find string matches even if certain characters are different or out of order, based on similarity value.
Tagger - Tag words in text according to specified rules or patterns. For example, tagging words based on which part of speech it belongs to.
Contribution
There are many potential improvements to be made to this library whether it be optimizing current modules, creating new modules or fixing bugs. For instance, the stemmer and stopwords modules use a predefined set of rules to perform their operations. These rule sets are still incomplete and can be expanded upon.
To propose any changes, simply open a pull request.
Bug reports, suggestions, questions, etc., can be done by creating a new issue.
Code formatting is done using black to ensure consistency.
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