Implementation of a Vector Space Retrieval Model using TF-IDF and cosine similarity on the Cranfield document corpus

Performs tokenization, stemming, lemmatization, index creation, index compression and ranked retrieval of Cranfield documents

An Information Retrieval System with 3 models and 3 datasets from the ir_datasets library .

Implementation of Salton and Buckley paper using 2 methods TF-IDF & Best Weighted Probabilistic

An advanced form of the previously implemented search Engine which acts as a information retrieval system over the cranfield collection of the 1400 documents and also makes use of the stemmer algorithm. Other things are pretty much the same as the previously implemented SearchEngine project.

Cranfield collection in TREC XML format.

Information Retrieval on Cranfield 1400 and NF-Corpus with Vector Space Model and Query Likelihood Model

📚 Information Retrieval Tutorial using Terrier with Cranfield collection

🔍 A Lucene demo for searching the Cranfield collection.

Python-based Information Retrieval system leveraging the BIM probabilistic model. Features include handling free-form text queries, relevance & pseudo-relevance feedback. Performance is rigorously evaluated using metrics like precision/recall, mean average precision, and R-precision. Utilizes the standard Cranfield dataset from aerodynamics.

Search Engine for the Cranfield Collection

Lucene SE for Cranfield Collection

Assignment from my MAI module 'Information Retrieval and Web Search' where I index the Cranfield Collection