Only recently have researchers been able to test and refine algorithms on vast data samples, including a huge trove of e-mail from the Enron Corporation.
“The economic impact will be huge,” said Tom Mitchell, chairman of the machine learning department at Carnegie Mellon University in Pittsburgh. “We’re at the beginning of a 10-year period where we’re going to transition from computers that can’t understand language to a point where computers can understand quite a bit about language.”
Nowhere are these advances clearer than in the legal world.
E-discovery technologies generally fall into two broad categories that can be described as “linguistic” and “sociological.”