suraphelalemu/Amharic-E-commerce

🛒 Building an Amharic E-commerce Data Extractor A comprehensive repository dedicated to extracting insights and data from Telegram channels, aimed at optimizing the e-commerce landscape in Ethiopia. 🔍 Overview This repository serves as a framework for leveraging Named Entity Recognition (NER) in the Amharic language, specifically tailored for e-commerce applications. Selected Channels are ZemenExpress, Fashiontera, nevacomputer, ethio_brand_collection, Shewabrand The following Ethiopian-based Telegram e-commerce channels have been selected for data ingestion: 📂 Project Structure +---.github | └── workflows | +---.vscode | └── settings.json +---notebooks | ├── data_processing.ipynb | ├── init.ipynb | └── README.md +---scripts | ├── data_labeler.py | ├── data_preprocessor.py | ├── data_scrapper.py | ├── init.py | └── README.md +---src | └── README.md | └── init.py +---tests | ├── README.md | └── init.py | ├── .gitignore | ├── labeled_data.conll | ├── README.md | └── requirements.txt 🛠️ Tools and Libraries Python: The primary programming language used for the implementation. Telethon: A Python library for interacting with Telegram’s API to scrape messages. Pandas: For data manipulation and storage in structured formats. NLTK or SpaCy: For text preprocessing and tokenization specific to Amharic linguistic features.