Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation

Author:

Mao Xinyu1ORCID,Zhuang Shengyao2ORCID,Koopman Bevan2ORCID,Zuccon Guido1ORCID

Affiliation:

1. The University of Queensland, Brisbane, Australia

2. CSIRO, Brisbane, Australia

Funder

Australian Research Council

Publisher

ACM

Reference53 articles.

1. Amal Alharbi, William Briggs, and Mark Stevenson. 2018. Retrieving and Rranking Studies for Systematic Reviews: University of Sheffield's Approach to CLEF eHealth 2018 Task 2. In Working Notes of CLEF 2018 - Conference and Labs of the Evaluation Forum, Vol. 2125.

2. Amal Alharbi and Mark Stevenson. 2017. Ranking Abstracts to Identify Relevant Evidence for Systematic Reviews: The University of Sheffield's Approach to CLEF eHealth 2017 Task 2. In Working Notes of CLEF 2017-Conference and Labs of the Evaluation Forum, Vol. 1866.

3. Amal Alharbi and Mark Stevenson. 2019. Ranking Studies for Systematic Reviews using Query Adaptation: University of Sheffield's Approach to CLEF eHealth 2019 Task 2. In Working Notes of CLEF 2019-Conference and Labs of the Evaluation Forum, Vol. 2380.

4. Antonios Anagnostou, Athanasios Lagopoulos, Grigorios Tsoumakas, and Ioannis Vlachavas. 2017. Combining Inter-Review Learning-to-Rank and Intra-Review Incremental Training for Title and Abstract Screening in Systematic Reviews. In Working Notes of CLEF 2017-Conference and Labs of the Evaluation Forum, Vol. 1866.

5. Tim Baumg"artner, Leonardo FR Ribeiro, Nils Reimers, and Iryna Gurevych. 2022. Incorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-Ranking. arXiv preprint arXiv:2210.10695 (2022).

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