From 928f30643d1640b45d008a8ec5a7c023c589904b Mon Sep 17 00:00:00 2001 From: Sanjaya Kumar Saxena Date: Fri, 9 Jul 2021 20:04:59 +0530 Subject: [PATCH] docs(README): update as per the revised documentation --- README.md | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 698dac0..139841c 100644 --- a/README.md +++ b/README.md @@ -13,29 +13,29 @@ winkNLP is a JavaScript library for Natural Language Processing (NLP). Designed ## Features It packs a rich feature set into a small foot print codebase of [under 1500 lines](https://coveralls.io/github/winkjs/wink-nlp?branch=master): -1. Lossless & multilingual tokenizer +1. Fast, lossless & multilingual [tokenizer](https://winkjs.org/wink-nlp/processing-pipeline.html) -2. Developer friendly and intuitive API +2. Developer friendly and intuitive [API](https://winkjs.org/wink-nlp/getting-started.html) -3. Built-in API to aid text visualization +3. Built-in [API](https://winkjs.org/wink-nlp/visualizing-markup.html) to aid [text visualization](https://observablehq.com/@winkjs/how-to-perform-sentiment-analysis?collection=@winkjs/winknlp-recipes) 4. Easy information extraction from raw text -5. Extensive text processing features such as bag-of-words, frequency table, stop word removal, readability statistics computation and many more. +5. Extensive [text processing features](https://winkjs.org/wink-nlp/its-as-helper.html) such as bag-of-words, frequency table, stop word removal, readability statistics computation and many more. -6. Pre-trained models with sizes starting from <3MB onwards +6. Pre-trained [language models](https://winkjs.org/wink-nlp/language-models.html) with sizes starting from <3MB onwards -7. BM25-based vectorizer +7. [BM25-based vectorizer](https://winkjs.org/wink-nlp/bm25-vectorizer.html) -8. Multiple similarity methods +8. Multiple [similarity](https://winkjs.org/wink-nlp/similarity.html) methods 9. Word vector integration -10. Comprehensive NLP pipeline covering tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech (pos) tagging, lemmatization, named entity extraction, custom entities detection and pattern matching +10. Comprehensive [NLP pipeline](https://winkjs.org/wink-nlp/processing-pipeline.html) covering tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech (pos) tagging, lemmatization, named entity extraction, custom entities detection and pattern matching -11. No external dependencies. +11. No external dependencies -12. Runs on web browsers +12. [Runs on web browsers](https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html). ## Installation @@ -57,7 +57,7 @@ node -e "require( 'wink-nlp/models/install' )" wink-eng-lite-model ``` ### How to install for Web Browser -If you’re using winkNLP in the browser use the [wink-eng-lite-web-model](https://www.npmjs.com/package/wink-eng-lite-web-model) instead. Learn about its installation and usage in our [guide to using winkNLP in the browser](https://winkjs.org/wink-nlp/how-to-run-wink-nlp-in-browser.html). +If you’re using winkNLP in the browser use the [wink-eng-lite-web-model](https://www.npmjs.com/package/wink-eng-lite-web-model) instead. Learn about its installation and usage in our [guide to using winkNLP in the browser](https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html). ## Getting Started The "Hello World!" in winkNLP is given below: