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---
title: Word Sense Disambiguation
emoji: π€
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
---
# π Hi, I'm Gunjankumar Nitin Choudhari
[](https://linkedin.com/in/gunjankumarchoudhari)
[](https://gunjankumar55.github.io/Gunjan_Portfolio/)
[](mailto:gunjankumarchoudhari@gmail.com)
[](https://youtube.com/@codespirit)
## π― About Me
I'm a B.Tech student at Ramrao Adik Institute of Technology, specializing in Computer Engineering with a focus on Data Science. With a strong CGPA of 9.40/10, I'm passionate about building intelligent systems and contributing to technological innovation.
## π Education
- **B.Tech in Computer Engineering (Data Science)**
Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University
CGPA: 9.40/10 | 2022 - Present
## π οΈ Tech Stack
- **Languages**: Python, Java, C, SQL, NoSQL, HTML, CSS, JavaScript
- **ML/AI**: TensorFlow, Scikit-learn, LLMs, Generative AI
- **Web**: Flask, JSP, Servlets
- **Mobile**: Flutter, Dart
- **Tools**: Git, Power BI, VS Code, Jupyter, LaTeX, Figma
- **Cloud**: Oracle Cloud, AWS
- **Databases**: MySQL, MongoDB
## π Certifications
- Oracle Cloud Infrastructure 2024 Generative AI Certified Professional
- Intel Unnati Training on AI
- Data Science for Engineers (NPTEL)
- Programming in Python (NPTEL)
- Alteryx Machine Learning Fundamentals
- Data Structure and Algorithms β Internshala
- PowerBI for Beginners - Simplilearn
## π Featured Projects
### 1. [AgrowAssist](https://github.com/Gunjankumar55/Agroassist---Smart-Crop-Recommendation-using-ML)
Smart Agricultural Assistance System with ML-powered crop recommendations
- 35% improved prediction accuracy
- Flutter mobile app with TensorFlow Lite
- Real-time disease detection
- Power BI data visualization
### 2. [AskDB](https://github.com/Gunjankumar55/askDB---Smart-text-to-sql-)
Natural Language to SQL Query Converter
- LLM-powered query conversion
- Flask backend with MySQL integration
- Responsive Bootstrap UI
- Efficient API communication
### 3. [LESK BERT WSD](https://github.com/Gunjankumar55/LESK_BERT_WSD)
Advanced Word Sense Disambiguation System
- BERT embeddings integration
- Enhanced Lesk algorithm
- Real-time feedback system
- Flask web interface
## πΌ Professional Experience
### Python Data Analyst Intern @ SPRINGBOARD
- Implemented ML algorithms improving prediction accuracy by 25%
- Created interactive Power BI dashboards
- Enhanced data visualization efficiency by 30%
### Java Development Trainee @ IT-Networkz Infosystem
- Developed MVC architecture web applications
- Optimized database operations with JDBC
- Improved performance speed by 30%
## π― Leadership & Activities
- Head of Design at CSI, RAIT
- Co-Head Design Officer at CSI, RAIT
- Co-Chief Design Officer at Social Wing, RAIT
- NSS Volunteer (2023-2024)
- Technical Content Creator on YouTube
## π GitHub Stats

## π± Currently Learning
- Advanced Generative AI
- Cloud Architecture
- System Design
- DevOps practices
## π― Goals
- Contribute to open-source projects
- Master full-stack development
- Build impactful AI applications
- Learn cloud technologies
## β‘ Fun Fact
When I'm not coding, you'll find me playing football, cricket, or creating graphic designs!
---
βοΈ From [Gunjankumar55](https://github.com/Gunjankumar55)
# LESK BERT WSD - Advanced Word Sense Disambiguation
[](https://www.python.org/)
[](https://flask.palletsprojects.com/)
[](https://www.nltk.org/)
[](https://huggingface.co/transformers/)
An advanced Word Sense Disambiguation (WSD) system that combines the Lesk algorithm with BERT embeddings for improved accuracy in determining word meanings from context.
## π Features
- **Enhanced Lesk Algorithm**: Improved version of the traditional Lesk algorithm
- **BERT Integration**: Uses BERT embeddings for better context understanding
- **Interactive Web Interface**: User-friendly Flask-based web application
- **Real-time Feedback System**: Learn from user corrections to improve accuracy
- **Context-Aware Processing**: Considers surrounding words and phrases
- **Multiple Sense Support**: Handles words with multiple meanings effectively
## π οΈ Technical Stack
- **Backend**: Flask, Python 3.9
- **NLP**: NLTK, BERT Transformers
- **Frontend**: HTML, CSS, JavaScript
- **Deployment**: Docker, Hugging Face Spaces
- **Version Control**: Git
## π Prerequisites
- Python 3.9+
- pip (Python package manager)
- Docker (for containerization)
## π Quick Start
1. Clone the repository:
```bash
git clone https://github.com/Gunjankumar55/LESK_BERT_WSD.git
cd LESK_BERT_WSD
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the application:
```bash
python app.py
```
4. Access the web interface at `http://localhost:5000`
## π‘ Usage
1. Enter a sentence containing an ambiguous word
2. The system automatically detects potential ambiguous words
3. Select a word to disambiguate
4. View detailed results including:
- Word definitions
- Example usage
- Confidence scores
- Alternative meanings
## π― Project Structure
```
LESK_BERT_WSD/
βββ app.py # Main application file
βββ requirements.txt # Project dependencies
βββ Dockerfile # Docker configuration
βββ templates/ # HTML templates
βββ static/ # Static assets
```
## π€ Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## π License
This project is licensed under the MIT License - see the LICENSE file for details.
## π¨βπ» Author
**Gunjankumar Choudhari**
- GitHub: [@Gunjankumar55](https://github.com/Gunjankumar55)
- LinkedIn: [Gunjankumar Choudhari](https://linkedin.com/in/gunjankumarchoudhari)
- Portfolio: [Gunjan Portfolio](https://gunjankumar55.github.io/Gunjan_Portfolio/)
## π Acknowledgments
- NLTK team for the excellent NLP tools
- Hugging Face for BERT implementation
- Flask team for the web framework |