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.

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.

Abstract: Embodiments of preservation solutions are presented herein. In particular, embodiments of such preservation solution may access a collaborative platform to preserve a collaborative content object by determining if any objects of a collaborative content object have been previously preserved. If none of the objects have been previously preserved, an archive for that collaborative content object may be created and stored. If, however, at least one of the objects of the collaborative object have been previously preserved, it can be determined if any objects of the compound content object have changed since the collaborative content object was previously preserved. An archive for only these changed objects (if any exist) may then be created and stored. Using these archives, at some point a review archive may be created and used to review the state of the collaborative content objects.