Overview of the TREC 2011 Legal Track

By Maura R. Grossman, Gordon V. Cormack, Bruce Hedin, Douglas W. Oard. 2011

31 citations recorded by the source corpus.

Subfields: Information Retrieval & Search, Natural Language Processing

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. Jimmy J. Lin
2. Rodrigo Nogueira
3. Andrew Yates
4. Haotian Zhang
5. Zeynep Akkalyoncu Yilmaz
6. Jamie Callan
7. Wei Yang
8. William Webber

In Natural Language Processing

1. Jimmy J. Lin
2. Rodrigo Nogueira
3. Haotian Zhang
4. Andrew Yates
5. William Webber
6. Douglas W. Oard
7. Mark D. Smucker
8. Maura R. Grossman

Citations in the corpus

• Pretrained Transformers for Text Ranking: BERT and Beyond (2020, background): “, 2006] to 2011 [Grossman et al., 2011], was organized to tackle this challenge.”
• Information Retrieval for E-Discovery (2013, methodology): “It was found that 70% recall could be achieved by productions of 1%, 3%, or 11% (across the three different topics) of the collection, but that participating systems were quite poor at actually picking the cutoff that achieved an optimal recall-precision tradeoff [60].”
• Evaluating sentence-level relevance feedback for high-recall information retrieval (2018, methodology): “The TREC Legal Track (2006–2011) (Baron et al, 2006; Tomlinson et al, 2007; Oard et al, 2008; Hedin et al, 2009; Cormack et al, 2010; Grossman et al, 2011) investigated HRIR methods for eDiscovery, which have come to be known as TAR.”