Text Similarity Test (using TensorFlow.js)

It outputs a percent similarity between two sentences.

This tool could possibly be used to check whether a free-form answer closely matches the expected answer in meaning. For best results, you probably should constrain responses to short sentences (i.e. short answer questions only).

Try it in your browser

https://codepen.io/hchiam/pen/oNjzQRa

Try it from your own computer

open index.html or yarn start or npm start

You can run useModelToEmbedAllSentences from CLI with node tfjs-stuff.js

Import it into your own project

<script src="https://cdn.jsdelivr.net/gh/hchiam/text-similarity-test@1.0.0/tfjs-stuff.js"></script>

var sentence1 = "Hello there!";
var sentence2 = "Hi, nice to see you!";
function callback(similarityScore) {
  alert(Math.round(similarityScore * 100 * 100) / 100 + "%");
}
useModel(sentence1, sentence2, callback); // useModel comes from tfjs-stuff.js

More things I'm testing

(See the coglangtext sub-folder.)

Useful references used

• https://github.com/tensorflow/tfjs-models/tree/master/universal-sentence-encoder
• https://towardsdatascience.com/how-to-build-a-textual-similarity-analysis-web-app-aa3139d4fb71
• https://github.com/jinglescode/demos/tree/master/src/app/components/nlp-sentence-encoder
• https://towardsdatascience.com/how-to-measure-distances-in-machine-learning-13a396aa34ce
• https://en.wikipedia.org/wiki/Cosine_similarity

Related repos

https://github.com/hchiam/learning-tensorflow

https://github.com/hchiam/text-similarity-test-microservice