Book Recommender System

Project Overview

This is a Book Recommender System that suggests books based on specific features from a dataset. Users can input the title of a book, and the system will return a list of 30 similar books.

Features Used for Recommendations

The system focuses on the following book attributes to generate recommendations:

• Title: The name of the book.
• Authors: The authors of the book.
• Categories: The genres or categories the book belongs to.
• Description: A brief summary or synopsis of the book.
• Published Year: The year the book was published.

How It Works

1. Input: The user enters the title of a book they like.
2. Processing: The system matches the input with books in the dataset, comparing features like title, authors, and categories.
3. Output: A list of up to 30 similar books is displayed to the user. If fewer than 30 books are found, or the input title doesn’t exist, an appropriate message is shown.

Dataset Information

The dataset includes various book attributes, such as:

• Title
• Authors
• Categories
• Thumbnail (cover image)
• Description
• Published Year

Future Enhancements

• Improving recommendation accuracy by fine-tuning the feature weighting.
• Allowing users to search based on different criteria (e.g., authors, categories).
• Adding collaborative-filtering components.

How to Run

1. Open this website and enter a book: https://an301.github.io/Book_Recommender/
2. Click button to get recommendations