E-Discovery AI Tools: Email Threading

E-Discovery Tools: Concept Search

• Machine learns the context in which words are used

• Mathematically models relationships among words.

• Users can search by meaning rather than by individual terms.

• Ex: search for “cups” would produce docs for “mugs” and “glasses.”

• Concepts vs. keywords

Example:

• “Do you want to watch the hockey game tonight, I bet the Krakens score”

• “Do you want to watch the game tonight, I bet the Krakens score”

E-Discovery Tools: Technology Assisted Review

“TAR”

• TAR/ predictive coding - widely available in eDiscovery software products today

• Algorithms that distinguish relevant from nonrelevant docs based on the coding of human reviewers and can then classify unlabeled documents on its own.