abel-hak/Amharic-natural-language-processing

# Amharic NLP Project Welcome to the **Amharic NLP Project**, where we explore the fascinating world of Amharic text analysis using a combination of traditional linguistic principles and modern Python libraries. This project aims to uncover patterns, frequencies, and semantic nuances of Amharic text, providing valuable insights and tools for researchers and developers. --- ## Table of Contents 1. Introduction 2. Features 3. Installation 4. Usage 5. Project Features - Remove Tags - Tokenization - Statistical Properties - Analysis of Words Based on Luhn's Idea - Normalization - Stopword Removal - Stemming - Inverted Index - Cosine Similarity 6. Visualization 7. Conclusion 8. Acknowledgments --- ## Introduction Amharic is a unique and rich language with its own challenges and opportunities in the field of Natural Language Processing (NLP). This project bridges linguistic tradition with technology by leveraging Python libraries such as: - **NLTK** for natural language processing tasks, - **NumPy** for efficient numerical operations, - **BeautifulSoup** for HTML/XML parsing, - **Matplotlib** for data visualization. This toolkit enables detailed analysis of Amharic text, from preprocessing to similarity analysis and visualization. --- ## Features - **HTML/XML Tag Removal:** Clean up raw text from web pages. - **Tokenization:** Break text into individual words while retaining Amharic structure. - **Normalization:** Standardize characters to reduce text variations. - **Stopword Removal:** Remove common Amharic stopwords. - **Stemming:** Reduce words to their root forms. - **Frequency Analysis:** Visualize word frequencies using Zipf's Law and Luhn's Idea. - **Inverted Index:** Map terms to document locations for efficient retrieval. - **Cosine Similarity:** Quantify similarity between documents. --- ## Installation 1. Clone this repository: ```bash git clone github.com cd amharic-nlp ``` 2. Install the required libraries …