ranked-retrieval

🔥 Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation 🔥. Our toolkit integrates 40 pre-retrieved benchmark datasets and supports 7+ retrieval techniques, 24+ state-of-the-art Reranking models, and multiple RAG methods.

UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction

An information retrival system for Persian language.

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

Implementation of Vector Space Model using TF-IDF and Cosine Similarity

Course Project of Information Retrieval.

SPIMI Ranked Retrieval Implementation and API

Interview My AI is an interactive portfolio experience where visitors can engage with my AI persona in a Q&A format. It showcases my knowledge, problem‑solving style, and communication skills, turning my portfolio into a dynamic interview space that highlights both technical depth and personal insight.

Final project of "Information Retrieval Systems" course

TTDS 2022/23. Course page: https://www.inf.ed.ac.uk/teaching/courses/tts/

A simple search engine built using Python 3.11 that implements TF-IDF weighting, page ranking, and cosine vector similarity, and utilizes NLTK libraries for tokenization and stemming.

This is lightweight Python-based information retrieval system that attempts to address an ad hoc retrieval task, in which a system provides documents from within a collection that are relevant to an arbitrary information need, communicated by means of a one-off user-initiated query.

Ranked Information Retrieval: an indexation and ranked retrieval system for textual information.

Wikimedia (enwiki) search engine built on inverted index and tf-idf ranked retrieval

A Simple Vector Space Model implementation for searching (some of) Donald Trump's speeches.

Implementing a search engine using Elastic-Search

An Information retrieval system for Persian news with ranked retrieval of documents according to relevance to the query.

This is a project that uses Information Retrieval concepts to develop a Search-as-a-Service Platform

An implementation for vector space models used in Information Retrieval for ranked retrieval. Uses TF, IDF, and normalizing on a textual dataset, mostly corpus from novels.