Information Retrieval Project

This project focuses on implementing and evaluating various information retrieval techniques using Python. The project includes scripts for indexing, query expansion, hybrid search, and semantic search.

Project Structure

• HYBRID-SEARCH.PY: This script performs a hybrid search using both lexical and semantic search engines. It combines the results using the Reciprocal Rank Fusion method and evaluates the retrieval performance.

• SEMANTIC-SEARCH.PY: This script creates a collection in ChromaDB using the SentenceTransformer model and evaluates the retrieval performance.

• QUERY-EXPANSION.PY: This script evaluates the query expansion method using the Signed Log-Likelihood Ratio (LLR) method.

• SIGNED-LLR.PY: This script contains functions to compute term frequencies, calculate LLR, and expand queries using the Signed LLR method.

• BM25.PY: This script runs the BM25 algorithm for the TREC-COVID dataset with different configurations and evaluates the retrieval performance.

• INDEXING.PY: This script is used to index a corpus of documents using the BM25 algorithm.

Setup

1. Clone the repository:

   git clone https://github.com/your-username/Information-Retrieval.git
   cd Information-Retrieval
   

Disclaimer

This was a project developed for the Information Repositories course of the University of Oviedo.

Mark obtained: 9.8 points over 10 possible points.