Applying text analytics to product innovation and legal cases

Adi Andrei, "Text analytics applied to product innovation"

How can text analytics combined with mining of sales data lead to creation of new successful products? The presentation is about a research in progress that explores this question. Preliminary results based on historical data of a couple of hand-picked product categories and thematics show the idea has promise. How can it be taken to the next level where this is done automatically? There are two major areas of inquiry: first, what is the best way to extract meaningful themes from product descriptions, and second how to detect meaningful new trends for these themes in literally a sea of data? Some possible solutions will be presented, but the hope is that the problem will spark interesting conversation and suggestions from the participants.

Adam Wyner and Wim Peters, "Lexical Semantics and Expert Legal Knowledge towards the Identification of Legal Case Factors"

Legal case factors are textually represented facts which are represented in reported legal case decisions. Precedent decisions contribute to the decision of a case under consideration. As textually represented facts, factors linguistically encode semantic properties and relationships among the entities which can be leveraged to identify and extract the legal case factors from decisions. We integrate legal and linguistic resources in a text analysis tool with which we annotate textual passages. Using annotations tailored to legal case factors, the legal researcher can rapidly zero in on textual spans which represent specific combinations of factors, participants, and semantic properties which bear on who played what role with respect to a factor. The research reports progress on the development of a tool.