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Semantic-Book-Recommender

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YuITC commited on Apr 17, 2025

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LICENSE +21 -0
README.md +55 -14
app.py +0 -11
cover-not-found.jpg +0 -0
data/books.csv +0 -0
data/books_cleaned.csv +0 -0
data/books_with_categories.csv +0 -0
data/books_with_emotions.csv +0 -0
data/full_desc.txt +0 -0
requirements.txt +17 -0
step_01_EDA.ipynb +0 -0
step_02_Vector_Search.ipynb +0 -0
step_03_Zero_Shot_Classification.ipynb +872 -0
step_04_Sentiment_Analysis.ipynb +671 -0
step_05_Gradio_Dashboard.py +122 -0

LICENSE ADDED Viewed

	@@ -0,0 +1,21 @@

+MIT License
+Copyright (c) 2025 Nguyen Phu Tai
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md CHANGED Viewed

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----
-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.
+![Screenshot 2025-04-17 232446](https://github.com/user-attachments/assets/045d2c52-3766-41df-86db-90d71b94b40f)
+## 🧠 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**:
+   ```bash
+   git clone https://github.com/YuITC/Semantic-Book-Recommender.git
+   cd Semantic-Book-Recommender
+   ```
+2. **Install dependencies**:
+   ```bash
+   pip install -r requirements.txt
+   ```
+3. **Run the Gradio dashboard**:
+   ```bash
+   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: tainguyenphu2502@gmail.com

app.py DELETED Viewed

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-import gradio as gr
-def greet(name):
-    return "Hello " + name + "!"
-demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
-if __name__ == "__main__":
-    demo.launch()

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