The Tensorflow implementation of accepted ACL 2018 paper "A deep relevance model for zero-shot document filtering", Chenliang Li, Wei Zhou, Feng Ji, Yu Duan, Haiqing Chen, http://aclweb.org/anthology/P18-1214

Pytorch implementation of CACM (WSDM'20)

Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering

EE448 Big Data Mining Project: Query Expansion with Rocchio Algorithm & Document Ranking with BM25 Score

ir_explain: a Python Library of Explainable IR Methods

This repo contains mini projects in Information Retrieval. Covers indexing, document ranking, web crawling, page ranking, and evaluating different models

🔝 HW1 of Intelligent Information Retrieval MSc Course ECE@UT

😷 Attempt on deep learning track challenge in TREC 2019 - https://microsoft.github.io/TREC-2019-Deep-Learning/

An information retrieval system for document ranking. Implementation and evaluation of Okapi BM25, Cosine Similarity, and Language Models for document ranking and retrieval. Includes precision-recall evaluation metrics and a detailed project report.

Scikit-learn implementation of co-occurrence word graph based semantic query search using machine learning and vector space similarity measures.

Probabilistic Reasoning and Bayes Rule; Text Data Analysis; Document Ranking and Evaluation.

Galago related homeworks of Information Retrieval Course

Implement the Pivoted Normalization and BM25 Retrieval Functions

A search engine that ranks documents by relevance to a query using a weighting scheme, tokenization, stop word removal, and stemming

Conducts query-independent document specificity scoring.

Assignment Submission for course Information Retrieval (CS F469)

This project implements a Document Retrieval System that integrates GPT-3.5-turbo for query expansion and answer generation. It fetches and ranks documents based on user queries, leveraging MongoDB for document storage, Redis for caching, and web scraping to keep documents updated. The system is designed to provide fast and accurate search results

IR implemented by using TF-IDF method

TinyBERT-based bi-encoder, cross-encoder, and poly-encoder trained on MS MACRO for passage re-ranking