Calculating similarity scores based on BERT embeddings among texts in batch
date
Dec 24, 2024
slug
calculating-similarity-scores-based-on-bert-embeddings-among-texts-in-batch
status
Published
summary
Using BERT embeddings, cosine similarity scores are calculated for textual contents in batches, with steps including data loading, model initialization, text retrieval, similarity score calculation, and visualization of results over time.
tags
Python
Academic
Engineering
Data Analysis
AI
type
Page
To resolve a recent issue in our research, I need to calculate a large volume of similarity scores of textual contents. I decided to use BERT and calculate the cosine similarity scores base on embeddings.
Here’s the steps.
Load the data
Load the model
Define a function to retrieve texts based on time
Calculate similarity scores
Run
Plot
By time:
