This repository is a curated list of resources for the field of Information Retrieval (IR), aimed at researchers, students, and practitioners. It provides a comprehensive overview of foundational and advanced topics, tools, and datasets to facilitate learning and development in building effective search and retrieval systems.

How It Works

The list is organized into categories including books, courses, software, datasets, talks, conferences, and blogs. It covers both traditional IR concepts and modern approaches, including those influenced by deep learning. The curated nature of the list aims to guide users through the vast landscape of IR resources, highlighting key materials and influential works.

Quick Start & Requirements

This is a curated list, not a software package. No installation or execution is required. Users can directly browse the provided links for books, courses, software, and datasets.

Highlighted Details

• Extensive list of seminal and contemporary books on Information Retrieval.
• Comprehensive collection of university courses and lectures from leading institutions like Stanford, CMU, and UT Austin.
• Detailed breakdown of TREC (Text REtrieval Conference) tracks, offering insights into specific IR evaluation tasks.
• Links to major IR software frameworks (e.g., Apache Lucene, Indri) and diverse datasets (e.g., Cranfield, GOV2, Reuters Corpora).

Maintenance & Community

The repository is maintained by Harshal Priyadarshi, with contributions welcomed via pull requests or email. The README encourages community involvement for adding new links and corrections.

Licensing & Compatibility

The content is provided under a public domain dedication (CC0 equivalent), allowing for unrestricted use and modification.

Limitations & Caveats

As a curated list, the quality and availability of linked resources are dependent on external sources. Some older datasets or software may require specific environments or have limited ongoing support.