Text REtrieval Conference (TREC)

Business Profile

Core Value Proposition

Text REtrieval Conference (TREC) provides an evaluation framework and community for measuring the effectiveness of search algorithms and other information retrieval technologies on large text collections. Data is free and participation is open.

Target Customer

Researchers and practitioners in information retrieval and natural language processing from academia, industry, and government labs who participate in TREC tasks and tracks.

Key Differentiator

Long-running, data-rich benchmarking ecosystem with free test collections and evaluation software; open participation; multiple tracks across diverse IR/NLP tasks; historically influential in advancing search technology.

Implementation Timeline

Access datasets and participate by registering for TREC 2025; participation leads to results-sharing at the TREC conference/workshop; the cycle culminates with a conference gathering.

Pain Points

1Need for standardized evaluation of information retrieval methods on large text collections
2Bridging research results to real-world search systems and products
3Lack of accessible, large-scale datasets and benchmarking tools for IR/NLP research

Key Features

1Free access to TREC data and evaluation software
2Open call for participation with 2025 registration available
3Multiple tracks (e.g., Adhoc Video Search, Biomedical, Generative Retrieval, RAG, etc.)
4Extensive published proceedings and decades of benchmark datasets

Target Customer Industries

Decision Makers

1{"title":"Program Manager","person":"Ian Soboroff"}
2{"title":"Contracting and Events","person":"Angela Ellis"}
3{"title":"Administrative Support","person":"Lawrence Deterville"}

Client Results

1Retrieval system effectiveness approximately doubled in the first six years of TREC
2Sponsorship and early evaluations of non-English document retrieval (Spanish and Chinese), speech retrieval, and cross-language retrieval
3Introduced evaluations for open-domain question answering and content-based retrieval of digital video
4Test collections and evaluation software made available to the research community

Competitive Advantages

1Free access to data and evaluation software
2Open participation and broad community involvement
3Decades of benchmark datasets and published proceedings
4Influence on the development of commercial search technologies

Key Benefits

1Standardized benchmarks for information retrieval performance

2Free datasets and evaluation software

3Open, collaborative community sharing results

4Proven influence on real-world search systems

Additional Product Information

Product Description

An evaluation workshop series organized by NIST (with DoD involvement) to measure information retrieval effectiveness on large text collections, providing datasets and benchmarks for researchers worldwide.

Target Market

Researchers in information retrieval and NLP across academia, industry, and government leveraging standardized benchmarks for evaluating and improving search technologies

Unique Value Proposition

Open, data-rich benchmarking framework that accelerates IR/NLP research-to-product transfer by providing free data, evaluation tools, and a global research community.

Technical Requirements

Access to TREC datasets and evaluation software; registration to participate; coordination and support provided by the NIST Retrieval Group

Pricing Model

Participation is free; TREC data is free.

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