Code and data for "Universal Approximation Functions for Fast Learning to Rank: Replacing Expensive Regression Forests with Simple Feed-Forward Networks"

Dataset and experiments from the CIKM 2020 Resource Track

Learning-to-Rank search engine combining BM25 retrieval with LambdaMART (LightGBM) for relevance-optimized document ranking. Achieves NDCG@10 of 0.9449 — a 6% improvement over baseline. Includes feature engineering pipeline and interactive Streamlit search UI.

UCL COMP0084 Information Retrieval and Data Mining (2023/24)

Bachelor Thesis 2024 - Automatic Identification of Duplicate Questions in Indonesian Consumer Health Forums Using Learning-to-Rank

A personalised news ranking system that learns and adapts to each user's preferences through interaction feedback such as clicks, dwell-time, likes, shares, and bookmarks.

Ranklib for .NET is an open source learning to rank library

A command line tool for training and evaluating ranking models using LightGBM and FastTree

An AI-native recruitment pipeline built for the IndiaRuns Hackathon. Features multi-threaded offline sentence-embeddings, graph-based career velocity mapping, proactive honeypot sweeping, and dynamic query-grouped LambdaMART ranking trees to evaluate 100,000 candidates with strict deterministic fairness.