International Business Machines Corporation
Extracting, deriving, and using legal matter semantics to generate e-discovery queries in an e-discovery system

Abstract:

Provided are techniques for extracting, deriving, and using legal matter semantics to generate e-discovery queries in an e-discovery system. A semantic knowledge graph is iteratively built by receiving meet and confer document instances, legal matter types, historical e-discovery queries for different legal matters, and legal semantic types extracted from the historical e-discovery queries. The legal semantic types are added to the semantic knowledge graph, and a list of terms that serve as a basis of an initial query are identified. An e-discovery query is generated for an e-discovery system. The e-discovery query is modified using the semantic knowledge graph and additional input by receiving a legal matter type and meet and confer information, obtaining the legal semantic types that are relevant to the legal matter type and the meet and confer information, and modifying the e-discovery query. The modified e-discovery query is provided. Then, the modified e-discovery query is executed.