Abstract: An example computing system may operate on episodes stored in an episodic memory using a semantic query language. The semantic query language may associate contextual labels with the data ingested from the data sources. Systems described herein may determine probabilities of an event based on the episodes including previous observations, counts, similarities, anomalies, and causality among many other techniques and methodologies. In some examples, the systems described herein may provide result explanations by providing references to source data pertinent to a given result. The user may provide feedback to the query results and update the semantic query.

Abstract: An example computing system may operate on episodes stored in an episodic memory using a semantic query language. The semantic query language may associate contextual labels with the data ingested from the data sources. Systems described herein may determine probabilities of an event based on the episodes including previous observations, counts, similarities, anomalies, and causality among many other techniques and methodologies. In some examples, the systems described herein may provide result explanations by providing references to source data pertinent to a given result. The user may provide feedback to the query results and update the semantic query.

Abstract: A computer data processing system including a central processing unit configured with a novel integrated computer control software system for the management of data objects including dynamic and automatic organization, linking, finding, cross-referencing, viewing and retrieval of multiple objects regardless of nature or source. The inventive system provides underlying component architecture having an object-oriented database structure and a metadata database structure which is unique in storing only one instance of each object while linking the object to multiple collections and domains by unique metadata links for the grouping into and retrieval from any of the collections. The system employs configurable, extensible attribute/properties of data objects in metadata format, and a truly user-friendly configurable interface that facilitates faster, more unified, comprehensive, useful and meaningful information management.