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https://github.com/mohdrasmil7/hotel-review-semantic-search
A web application built using spaCy for semantic searching 🧠🔍, allowing users to input queries and retrieve contextually relevant results 📄✨. Features a user-friendly interface and efficient processing 🚀.
https://github.com/mohdrasmil7/hotel-review-semantic-search
Last synced: about 2 months ago
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A web application built using spaCy for semantic searching 🧠🔍, allowing users to input queries and retrieve contextually relevant results 📄✨. Features a user-friendly interface and efficient processing 🚀.
- Host: GitHub
- URL: https://github.com/mohdrasmil7/hotel-review-semantic-search
- Owner: MohdRasmil7
- Created: 2024-10-22T14:43:12.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-10-31T08:05:50.000Z (2 months ago)
- Last Synced: 2024-10-31T09:17:44.435Z (2 months ago)
- Language: HTML
- Homepage:
- Size: 26.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Semantic Search System
## Overview
This project implements a **Semantic Search System** using **spaCy**, an advanced natural language processing library in Python. The application allows users to perform semantic searches, retrieving relevant results based on the meaning of their queries.
## Features
- **Semantic Search**: Users can input queries, and the system retrieves results that are contextually relevant.
- **User-Friendly Interface**: A clean and simple front-end for easy interaction with the tool.
- **Fast and Efficient**: Utilizes spaCy’s powerful NLP capabilities for quick processing.
## Technologies Used
- **Python**: The programming language used for backend development.
- **spaCy**: The NLP library for processing and understanding text.
- **Flask**: The web framework used for developing the web application.
- **HTML/CSS/JavaScript**: Technologies used for the front-end development.
## Installation
To run this project locally, follow these steps:
1. **Clone the repository**:
```bash
git clone [Link to your GitHub repository]
```
2. **Navigate to the project directory**:
```bash
cd semantic-search-system
```
3. **Install the required packages**:
```bash
pip install -r requirements.txt
```
4. **Run the application**:
```bash
python app.py
```
5. **Open your browser and go to**: [http://127.0.0.1:5000](http://127.0.0.1:5000)
## Usage
1. Enter your query in the input box.
2. Click on the "Search" button.
3. The system will return relevant results based on the meaning of your query.
## Challenges Faced
- **Understanding spaCy**: Initially, there was a learning curve in understanding how to effectively utilize spaCy for semantic searching.
- **Performance Optimization**: Ensuring the search results were returned quickly and accurately required several iterations of testing and refining the model.
## Conclusion
This project showcases the capabilities of spaCy in building a semantic search tool. It provides a foundation for further enhancements, such as adding more complex query processing or integrating machine learning models for better accuracy.
## Acknowledgements
- [spaCy Documentation](https://spacy.io/usage)
- [Flask Documentation](https://flask.palletsprojects.com/)