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    <abstract>Technology Assisted Review (TAR) stopping rules aim to reduce the cost of manually assessing documents for relevance by minimising the number of documents that need to be examined to ensure a desired level of recall. This paper extends an effective stopping rule using information derived from a text classifier that can be trained without the need for any additional annotation. Experiments on multiple data sets (CLEF e-Health, TREC Total Recall, TREC Legal and RCV1) showed that the proposed approach consistently improves performance and outperforms several alternative methods.</abstract>
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    <identifier type="doi">10.18653/v1/2023.findings-emnlp.171</identifier>
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%0 Conference Proceedings
%T Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review
%A Bin-Hezam, Reem
%A Stevenson, Mark
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Findings of the Association for Computational Linguistics: EMNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F hezam-stevenson-2023-combining
%X Technology Assisted Review (TAR) stopping rules aim to reduce the cost of manually assessing documents for relevance by minimising the number of documents that need to be examined to ensure a desired level of recall. This paper extends an effective stopping rule using information derived from a text classifier that can be trained without the need for any additional annotation. Experiments on multiple data sets (CLEF e-Health, TREC Total Recall, TREC Legal and RCV1) showed that the proposed approach consistently improves performance and outperforms several alternative methods.
%R 10.18653/v1/2023.findings-emnlp.171
%U https://aclanthology.org/2023.findings-emnlp.171
%U https://doi.org/10.18653/v1/2023.findings-emnlp.171
%P 2603-2609

Markdown (Informal)

[Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review](https://aclanthology.org/2023.findings-emnlp.171) (Bin-Hezam & Stevenson, Findings 2023)

• Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review (Bin-Hezam & Stevenson, Findings 2023)

ACL

• Reem Bin-Hezam and Mark Stevenson. 2023. Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 2603–2609, Singapore. Association for Computational Linguistics.