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---
title: Book Recommender
emoji: ๐Ÿ“‰
colorFrom: gray
colorTo: blue
sdk: streamlit
sdk_version: 1.41.1
app_file: app.py
pinned: false
short_description: A basic book recommender system
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# Content-Based Book Recommender System
This is a content-based book recommender system built using **Streamlit**. It takes a book title as input and generates up to 5 recommendations based on content similarity. The recommendations combine textual similarity (TF-IDF) and semantic similarity (Sentence Transformers). The system also handles typos and invalid inputs.
---
## Features
1. **Content-Based Recommendations**:
- Combines TF-IDF and semantic similarity to recommend books.
- Handles typos and approximate matches using fuzzy matching.
2. **Error Handling**:
- Ensures graceful failure for invalid inputs or system errors.
- Provides fallback recommendations when similarity scores are insufficient.
3. **Interactive UI**:
- Built with Streamlit for a user-friendly interface.
## Dependencies and Functionality
1. pandas:
Handles data loading, preprocessing, and manipulation.
2. scikit-learn:
Provides TF-IDF vectorization and NearestNeighbors for similarity search.
3. sentence-transformers:
Generates semantic embeddings for textual data.
4. numpy:
Used for numerical computations like handling embeddings and arrays.
5. streamlit:
Creates the interactive UI for the application.
6. rapidfuzz:
Implements fuzzy matching for typos and approximate title matches.
7. re:
Cleans special characters from book titles.