Overview of the Seventh Text REtrieval Conference

By Ellen M. Voorhees. 1998

Subfields: Information Retrieval & Search, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Retrieval & Search

1. Mark Sanderson
2. Shaul Markovitch
3. Idan Szpektor
4. Bernardo Magnini
5. Evgeniy Gabrilovich
6. Ofer Egozi
7. Eero Sormunen
8. Danilo Giampiccolo

In Evaluation & Benchmarks

1. Ido Dagan
2. Bernardo Magnini
3. Idan Szpektor
4. Christopher D. Manning
5. Bill Dolan
6. Danilo Giampiccolo
7. Mark Sanderson
8. Samuel R. Bowman

Citations in the corpus

• The Third PASCAL Recognizing Textual Entailment Challenge (2007, background): “in information retrieval), and is computed as the average of the system’s precision values at all points in the ranked list in which recall increases, that is at all points in the ranked list for which the gold standard annotation is YES (Voorhees and Harman, 1999).”
• Concept-Based Information Retrieval Using Explicit Semantic Analysis (2011, methodology): “In Proceedings of the 7th Text REtrieval Conference (TREC-7).”
• Performance evaluation in content-based image retrieval: overview and proposals (2001, background): “The TREC project (see TRE (1999), Vorhees & Harmann (1998)) provides a focus for these activities and is the worldwide standard in IR.”
• Recognizing textual entailment: Rational, evaluation and approaches – Erratum (2010, unknown): “…common evaluation measure for ranking (e.g. in IR) and is computed as the average of the system’s precision values at all points in the ranked list in which recall increases, that is to say at all points in the ranked list for which the gold-standard annotation is ‘yes’ (Voorhees and Harman 1999).”
• Liberal relevance criteria of TREC -: counting on negligible documents? (2002, methodology): “In TREC, for example, the pooling method was developed to guarantee that the list of documents assessed for relevance is as comprehensive as possible [ 13 , 14].”
• The Second PASCAL Recognising Textual Entailment Challenge (2006, background): “…measure for ranking (e.g. in information retrieval), and is computed as the average of the system's precision values at all points in the ranked list in which recall increases, that is at all points in the ranked list for which the gold standard annotation is YES (Voorhees and Harman, 1999).”