README.md

metadata

title: Semantic Book Recommender
emoji: 📊
colorFrom: indigo
colorTo: yellow
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
license: mit
short_description: A Semantic Book Recommendation System using LLM.

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Semantic Book Recommender

A semantic-based book recommendation system leveraging modern NLP techniques to provide context-aware suggestions.

🧠 Project Overview

This project explores the application of Natural Language Processing (NLP) and Large Language Models (LLMs) in building a semantic book recommender system. The system goes beyond traditional keyword-based recommendations by understanding the contextual meaning of book descriptions and user preferences.

📁 Project Structure

• data/: Contains the dataset used for analysis and model training.
• step_01_EDA.ipynb: Performs Exploratory Data Analysis to understand data distribution and key features.
• step_02_Vector_Search.ipynb: Implements vector-based search using sentence embeddings to find semantically similar books.
• step_03_Zero_Shot_Classification.ipynb: Applies zero-shot classification to categorize books without labeled data, utilizing pre-trained LLMs.
• step_04_Sentiment_Analysis.ipynb: Conducts sentiment analysis on book reviews to gauge reader opinions.
• step_05_Gradio_Dashboard.py: Develops an interactive dashboard using Gradio for users to input preferences and receive recommendations.
• requirements.txt: Lists all Python dependencies required to run the project.

🔍 Key Features

• Semantic Search: Utilizes sentence embeddings to capture the semantic meaning of book descriptions, enabling more accurate recommendations.
• Zero-Shot Classification: Employs pre-trained LLMs to classify books into genres or categories without the need for labeled training data.
• Sentiment Analysis: Analyzes user reviews to understand the general sentiment towards books, aiding in recommendation decisions.
• Interactive Dashboard: Provides a user-friendly interface for users to input their preferences and receive tailored book suggestions.

🚀 Getting Started

1. Clone the repository:

   git clone https://github.com/YuITC/Semantic-Book-Recommender.git
   cd Semantic-Book-Recommender
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the Gradio dashboard:

   python step_05_Gradio_Dashboard.py
   

📜 License

This project is licensed under the MIT License – feel free to modify and distribute it as needed.

🤝 Acknowledgments

If you find this project useful, consider ⭐️ starring the repository or contributing to further improvements!

📬 Contact

For any questions or collaboration opportunities, feel free to reach out:

📧 Email: [email protected]