Abstract :
In a low-rise building in Menlo Park, Calif., just upstairs from a Mexican restaurant and a nail salon, a Stanford University spin-off is crunching data in ways that could shake the foundations of the legal profession.Here, a small group of patent lawyers and computer scientists is applying the latest in machine learning and natural-language processing to reams of documents related to intellectual property lawsuits. The result is a massive statistical database on IP litigation like nothing the world has seen before.Which attorney has the best track record in defending against semiconductor-related infringement claims? Has a particular judge ruled on cases involving patent trolls, and if so, what was the outcome? Which companies tend to go to trial, and which settle out of court? By offering up such information, the database provides corporate lawyers, law lirms, and government agencies with hard numbers that will reduce the guesswork, as well as the enormous expense, of patent litigation. In short, the company is building a “law machine,” from whichcomes its name: Lex Machina.
Keywords :
document handling; industrial property; learning (artificial intelligence); legislation; natural language processing; statistical databases; IP litigation; Lex Machina; Stanford University spin-off; computer scientists; corporate lawyers; government agency; intellectual property lawsuits; intellectual property litigation; law firms; law machine; legal profession; machine learning; massive statistical database; natural-language processing; patent lawyers; patent litigation; Data processing; Database systems; Intellectual property; Law; Legal aspects;