The active learning workflow in Relativity Assisted Review continuously learns what’s important to your matter, refining its understanding of what’s responsive and getting smarter as the review progresses. While it’s easy for users to get up and running with active learning, a lot happens behind the scenes. This paper explores the technology behind the active learning workflow as well as how it works from beginning to end.
Download this white paper to learn:
- The algorithm behind active learning
- The elements of active learning and how you can incorporate it into your workflow
- Monitoring and validating your project to ensure your results are accurate