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
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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