natural VS retext

Compare natural vs retext and see what are their differences.

natural

general natural language facilities for node (by NaturalNode)

retext

natural language processor powered by plugins part of the @unifiedjs collective (by retextjs)
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natural retext
4 2
10,473 2,331
0.3% 0.3%
8.2 6.5
6 days ago 7 months ago
JavaScript JavaScript
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

natural

Posts with mentions or reviews of natural. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-21.

retext

Posts with mentions or reviews of retext. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-02.

What are some alternatives?

When comparing natural and retext you can also consider the following projects:

nlp.js - An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more

franc - Natural language detection

Brain.js - Simple feed-forward neural network in JavaScript

machine-translator - Translate words using a statistical model

Tesseract.js - Pure Javascript OCR for more than 100 Languages 📖🎉🖥

text2token - break down a corpus of text into lines and tokens

leven - Measure the difference between two strings with the fastest JS implementation of the Levenshtein distance algorithm

Synaptic.js - architecture-free neural network library for node.js and the browser

unified - ☔️ interface for parsing, inspecting, transforming, and serializing content through syntax trees