# Ethiopian-News-Information-Retrieval-System
The Ethiopian News Information Retrieval System aims to enhance access to Amharic news articles by
implementing an efficient document retrieval framework. The primary objective was to develop a
system that effectively indexes and retrieves relevant documents based on user queries, utilizing
techniques such as text normalization, tokenization, stemming, and the BM25 ranking algorithm.
The system was built using Python with Flask as the web framework, enabling a user-friendly interface
for search functionality. A collection of Amharic news documents was processed to create an inverted
index, which facilitates quick lookups and retrievals. Evaluation metrics, including precision, recall,
F1-score, Mean Average Precision (MAP), Normalized Discounted Cumulative Gain (NDCG), and
Mean Reciprocal Rank (MRR), were employed to assess performance.