/Quotes-Recommendation-System

Quotes Recommendation System using a BERT model

Primary LanguageJupyter Notebook

Quotes Recommendation System

This is a Quotes Recommendation System that uses the BERT model to provide two types of recommendations based on a dataset of English quotes from Abirate/english_quotes:

  • Recommend quotes by topic: Given a topic, the model recommends quotes related to the topic.
  • Recommend similar quotes: Given a quote, the model recommends the most similar quotes.

Model

The model used is bert-base-uncased, a pre-trained model that is commonly used for text classification tasks. The BERT model is fine-tuned on the English quotes dataset, then we calculate similarity scores between quotes.

Recommendation Modules

The recommendation system includes two modules:

  • Topic-based Recommendation Module: This module recommends quotes based on the input topic. It works by calculating the similarity scores between the input topic and all quotes in the dataset and returning the top N quotes with the highest similarity scores.

  • Quote-based Recommendation Module: This module recommends quotes based on the input quote. It works by calculating the similarity scores between the input quote and all quotes in the dataset and returning the top N quotes with the highest similarity scores.