Ricoh has embraced Relativity’s Active Learning. Joining Mark Anderson and Bill Belt of CDS, were Zoe Davies, Legal eDiscovery Manager at Barclays; Jeffrey Shapiro, eDiscovery Manager at Clifford Chance; and Paul Gordon, International Solutions at Relativity. Continuous Ranking Insight Predict can rank millions of documents in minutes.
It was used in a case with extremely successful results and Ricoh had just published a case study about the matter.
Combine email threading, clustering, sample-based learning, and visualisations with active learning to create unique workflows that match the needs of your project—whether it’s investigating the merits of a claim, sorting your data into key issues or preparing evidence for litigation. There is a larger version of the case study here. Based on user feedback of the new Relativity Continuous Active Learning review queue i would propose an alternative review queue behavior that would allow for higher quality user experience. The article gives a brief description of what Continuous Active Learning is. Only 4% of the documents were served up to the reviewers, 95% of which were relevant. More significantly, perhaps, it has a section called How to use continuous active learning – size doesn’t matter , which sets out some of the factors to consider when using Continuous Active Learning including, crucially, discussions aimed at “explaining and justifying strategy to the other side”.
Clients and customers expect their lawyers and law firms to do more than ever, managing and parsing an unprecedented volume of data quickly and effectively. One bit of feedback we've received from reviewers is that they dont like the "random" nature of the documents. Active learning is the new kid on a block full of unstructured and structured analytics tools.
Relativity is the most comprehensive eDiscovery platform to organise and interpret large volumes of data and identify key issues in investigations, litigation or compliance. TAR 2.0 and Continuous Active Learning These real-world problems disappear with Insight Predict, our TAR 2.0 engine that uses continuous ranking and Continuous Active Learning to reduce review time and costs while also making the process more fluid and flexible. The world of eDiscovery is at a tipping point. Relativity is a well adopted review platform and we expect that the integration with Sentio Software Predictive Analytics will help Relativity users realize the power of Continuous Active Learning functionality by increasing the accuracy of the review as well as …
Relativity has written about the case here.
Last week, Complete Discovery Source’s London office hosted a breakfast seminar on Continuous Active Learning (CAL). Relativity features advanced analytics, machine learning and continual enhancement including: Email threading; Continuous active learning