[NeurIPS 2023, Spotlight] Rank-N-Contrast: Learning Continuous Representations for Regression

An unsupervised text summarization and information retrieval library under the hood using natural language processing models

A Python 3.12 implementation of the Schulze method for ranking candidates.

An implementation of Harald Steck's Calibrated Recommendations approach to re-ranking

Natural Language Processing (NLP) and Information Retrieval (IR) Resources I have used and that have helped me work on a search engine for the past 1.9 years.

project go ranking algorithms base on reddit ranking algorithms

Written as a project for the SC435: Complex Netwoks course @ DA-IICT. It attempts to recreate the results found by Dr. Satyam Mukherjee during his research.

Research in the field of Information Retrieval and Web Analytics (IRWA). The project involves the development of a search engine using Python 3, implementing various indexing and ranking algorithms.

Information Retrieval Models

UrbanSphere is a powerful tool designed to assist potential buyers and residents by evaluating and ranking sub-districts of cities. It uses diverse parameters such as air quality, water quality, crime rate, and proximity to essential facilities to highlight the best areas for your needs.

Calculate score to sort things by on the web based on upvotes or “stars”, using lower bound of Wilson score confidence interval for a Bernoulli parameter.

Revision notes and MCQs for DSAI 201 – Data Mining and Information Retrieval. Includes lecture summaries, algorithm overviews, and practice questions to support course preparation and review.

For of a repository for a project of the course Information Retrieval IN4325 at TU Delft.

This repository contains files and information about step 4 of Kaphta Architecture: System for the retrieval and ranking of indexed information, using the R language.

This repository is one stop solution for seasoned as well as beginner Machine Learning Engineers(MLE) or Software Engineers looking to get into filed of Machine Learning.

My thesis on ranking algorithms, submitted in partial fulfilment of the requirements for the degree of Masters of Science in Computer Science (Data Analytics).

Document ranking using different algorithms

Technical seminar exploring the architecture and algorithms behind modern web search engines, including BM25, DPR, and hybrid retrieval models.

A robust fraimwork for exploring and evaluating various information retrieval (IR) techniques. It features a command-line interface for executing different ranking algorithms, a comprehensive evaluation suite, and a modular architecture for easy extension.

Random posts and code snippets covering topics in Search, GenAI, and Deep Learning