11 citations · 15 across the 6 of their papers we have counts for
6 papers
Confidence-Based Stopping Methods for Systematic Reviews
Aaron Fletcher, Mark Stevenson
Technology Assisted Review stopping methods aim to ensure that no more documents are screened than necessary. Most existing approaches focus on achieving a target recall, which doe…
Decision-Theoretic Stopping Rules for Document Screening
Aaron H. A. Fletcher, Mark Stevenson
Deciding when to stop reviewing the results of a search is a common problem with multiple applications. Existing stopping rules developed within Technology-Assisted Review (TAR) ai…
A Generalised and Adaptable Reinforcement Learning Stopping Method
Reem Bin-Hezam, Mark Stevenson
This paper presents a Technology Assisted Review (TAR) stopping approach based on Reinforcement Learning (RL). Previous such approaches offered limited control over stopping behavi…
RLStop: A Reinforcement Learning Stopping Method for TAR
Reem Bin-Hezam, Mark Stevenson
We present RLStop, a novel Technology Assisted Review (TAR) stopping rule based on reinforcement learning that helps minimise the number of documents that need to be manually revie…
Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review
Reem Bin-Hezam, Mark Stevenson
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…
Stopping Methods for Technology Assisted Reviews based on Point Processes
Mark Stevenson, Reem Bin-Hezam
Technology Assisted Review (TAR), which aims to reduce the effort required to screen collections of documents for relevance, is used to develop systematic reviews of medical eviden…