The Text REtrieval Conferences (TRECs)

Authors:
Donna Harman
Affiliations:
National Institute of Standards and Technology, Gaithersburg, MD
Venue:
TIPSTER '96 Proceedings of a workshop on held at Vienna, Virginia: May 6-8, 1996
Year:
1996

Citing 6
Cited 3

Reflections on TREC

TREC-2 Proceedings of the second conference on Text retrieval conference
Searching distributed collections with inference networks

SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using local and global document analysis

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Pivoted document length normalization

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A new method of weighting query terms for ad-hoc retrieval

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval

Introduction to Modern Information Retrieval

The effects of query structure and dictionary setups in dictionary-based cross-language information retrieval

Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Some thoughts on the reported results of TREC

Information Processing and Management: an International Journal
Discovery of Context-Specific Ranking Functions for Effective Information Retrieval Using Genetic Programming

IEEE Transactions on Knowledge and Data Engineering

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Abstract

There have been four Text REtrieval Conferences (TRECs); TREC-1 in November 1992, TREC-2 in August 1993, TREC-3 in November 1994 and TREC-4 in November 1995. The number of participating systems has grown from 25 in TREC-1 to 36 in TREC-4, including most of the major text retrieval software companies and most of the universities doing research in text retrieval (see table for some of the participants). The diversity of the participating groups has ensured that TREC represents many different approaches to text retrieval, while the emphasis on individual experiments evaluated in a common setting has proven to be a major strength of TREC.