Overview of the TREC-2012 Microblog Track
By Ian Soboroff, Iadh Ounis, Craig Macdonald, Jimmy J. Lin. 2014
141 citations recorded by the source corpus.
Subfields: Natural Language Processing, 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 Natural Language Processing
- Jimmy J. Lin
- Aliaksei Severyn
- Alessandro Moschitti
- Rodrigo Nogueira
- Andrew Yates
- Garrick Sherman
- Yulu Wang
- Miles Efron
In Evaluation & Benchmarks
- Jimmy J. Lin
- Garrick Sherman
- Yulu Wang
- Aliaksei Severyn
- Miles Efron
- Rodrigo Nogueira
- Andrew Yates
- Alessandro Moschitti
Citations in the corpus
- Pretrained Transformers for Text Ranking: BERT and Beyond (2020, background): “oiding it. An earlier work [Yang et al., 2019e] that eventually gave rise to Birch first examined the task of ranking tweets, using test collections from the TREC Microblog Tracks [Ounis et al., 2011, Soboroff et al., 2012, Lin and Efron, 2013, Lin et al., 2014]. These evaluations focused on informat”
- Overview of the TREC-2014 Microblog Track (2014, methodology): “We refer the reader to previous track overview papers [8, 12, 9] for details on the setup of the ad hoc task.”
- ReQ-ReC: high recall retrieval with query pooling and interactive classification (2014, methodology): “MB12 MB13 ClueWeb09 HARD 20NG µ 2100 - - 1100 3200 β 0.95 0.85 0.75 0.6 0.5 γ 0.4 0.15 0.15 0.05 0.4 Results/query 2,000 10,000 1,000 2,000 2,000 under the ReQ-ReC framework significantly outperform iterative relevance feedback.”
- Overview of the TREC-2013 Microblog Track (2013, methodology): “[2] I.”
- Adaptive Method for Following Dynamic Topics on Twitter (2014, methodology): “More work on tracking tweets on focused topics has been reported for the TREC microblog track that has introduced a filtering task for the first time in 2012 (Soboroff et al., 2012).”
- Modelling input texts: from Tree Kernels to Deep Learning (2015, methodology): “We focus on the 2011 and 2012 editions of the ad-hoc retrieval task at TREC microblog tracks [103, 149].”
- Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks (2015, methodology): “We focus on the 2011 and 2012 editions of the ad-hoc retrieval task at TREC microblog tracks [23, 29].”