Abstract: In one aspect, the present disclosure relates to a method which, in one example embodiment, can include receiving text data that includes at least unstructured data and wherein the text data is associated with a plurality of messages communicated between a plurality of entities. The method can also include determining relationships between the entities, based on the text data associated with the plurality of messages, and generating, from a knowledge base assembled from at least the text data, a response to a user interaction representing a query for information that corresponds to at least one of the entities and indicates information on one or more of the determined relationships between the entities. The method can also include detecting a deviation in communication between the entities that indicates unauthorized disclosure of information between a first entity and a second entity.

Abstract: In one aspect, the present disclosure relates to a method which, in one example embodiment, can include reading text data corresponding to messages and creating semantic annotations to the text data to generate annotated messages. Creating the semantic annotations can include generating, at least in part by at least one trained statistical language model, predictive labels as annotations corresponding to language patterns associated with the text data. The method further includes aggregating the annotated messages and storing information associated with the aggregated annotated messages in a message store, and performing, based on information from the message store and associated with the messages, global analytics functions.

Abstract: In one aspect, the present disclosure relates to a method which, in one example embodiment, can include reading text data corresponding to messages and creating semantic annotations to the text data to generate annotated messages. Creating the semantic annotations can include generating, at least in part by at least one trained statistical language model, predictive labels as annotations corresponding to language patterns associated with the text data. The method further includes aggregating the annotated messages and storing information associated with the aggregated annotated messages in a message store, and performing, based on information from the message store and associated with the messages, global analytics functions.

Abstract: In one aspect, the present disclosure relates to a method which, in one example embodiment, can include reading text data corresponding to messages, creating semantic annotations to the text data to generate one or more annotated messages, and aggregating the annotated messages and storing information associated with the aggregated annotated messages in a message store. The method can further include performing, based on information from the message store and associated with the one or more messages, one or more global analytics functions that include: identifying an annotation error in the semantic annotations created using the trained statistical language model, updating the respective semantic annotation to correct the annotation error, and back-propagating corrected data corresponding to the updated semantic annotation into training data for further language model training.