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Found 3 papers, 2 papers with code
RLStop: A Reinforcement Learning Stopping Method for TAR
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 reviewed within TAR applications.
Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review
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.
Stopping Methods for Technology Assisted Reviews based on Point Processes
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 evidence and identify documents that must be disclosed in response to legal proceedings.
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