Raytheon Bbn Technologies Corp.

Ilana Heintz

Bonan Min

Yee Seng Chan

John Grothendieck

Jessica MacBride

Newton Henry Campbell, Jr

A machine accesses a preexisting set of natural language text documents in multiple natural languages. Each natural language text document in at least a portion of the preexisting set is associated with an event. The machine trains, using the preexisting set of natural language text documents and the associated events, an event encoder to learn associations between texts and event annotations. The event encoder leverages a parser in each of the two or more natural languages. The machine generates, using the event encoder, new event annotations for texts. The machine trains, using the preexisting set of natural language text documents and the new event annotations for the texts generated by the event encoder, an event extraction engine to extract events from natural language texts in the two or more natural languages. The event extraction engine leverages the parser in each of the two or more natural languages.

Linguistically rich cross-lingual text event embeddings

A technique is described including taking a research paper of interest (target paper) and identifying concepts within it based on topic analysis among bibliometric clusters; identifying descriptions of each concept across bibliometric clusters wherein the descriptions will be of varying levels of granularity and will use different terms to describe the same concept or phenomena; using the various descriptions of a concept to create search terms to be used in a repository of annotated, searchable source code snippets; and constructing implementation of target paper's methodologies using source code snippets.

Method and system for extracting concepts from research publications to identify necessary source code for implementation

Aspects are generally directed to network security systems and methods of monitoring network activity. In one example, a network security system includes and interface to receive a Hypertext Transfer Protocol (HTTP) network log that includes a matrix of data, a feature extraction component configured to extract a connectivity matrix from the HTTP network log based on a recurring pattern within the matrix of data, and a training module configured to provide deep learning architecture training data based on the connectivity matrix. The system may include a deep learning architecture configured to receive and propagate the training data through one or more layers thereof to train the one or more layers, and being configured to generate a general data representation of the HTTP network log. The system may include a behavior analytics component to detect a discordant network activity within the HTTP network log based on the general data representation.

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Silver Spring, MD, United States of America

Ilana Heintz