Digital Reasoning Systems, Inc.

Other

Kenneth Loran Graham

Vishnuvardhan Balluru

Phillip Daniel Michalak

Keith Ellis Massey

John Wagster

James Johnson Gardner

Sarah Cannon

Naomi Hilliard

Robert Metcalf

Adam Jaggers

Bill Dipietro

James Zamata

Holly Gardner

Some aspects of the present disclosure relate to systems and methods for identifying potential violation conditions from electronic communications. In one embodiment, a method includes receiving data associated with an electronic communication and detecting, from the received data, and using a trainable model, an indicator of a potential violation condition, where the violation condition is associated with an activity that is a violation of a predetermined standard. The method also includes, responsive to detecting the indicator of the potential violation condition, marking the electronic communication as being associated with a potential violation condition, and presenting the potential violation condition to a user for review. The method also includes receiving a decision from the user, based on the review, on whether the electronic communication is associated with a violation condition, and based on the decision, improving the model for detecting potential violation conditions in other electronic communications.

Systems and methods for identifying violation conditions from electronic communications

In some aspects, systems, methods, and computer-readable media for selective feature activation for coreference resolution are disclosed. In one embodiment, a method includes receiving text data comprising a plurality of mentions corresponding to entities, and determining a plurality of data features, comprising semantic features and syntactic features, for comparing a particular pair of mentions from the plurality of mentions. The method also includes selectively activating a subset of features from the plurality of data features based on semantic and syntactic context of the particular pair of mentions within the text data, and determining, using weights associated with the activated subset of features and at least one machine learning function, whether a first mention of the pair of mentions and second mention of the pair of mentions refer to a same entity.

Systems and methods for coreference resolution using selective feature activation

In some aspects, the present disclosure relates to coreference resolution. In one embodiment, a method includes obtaining unstructured text data including a plurality of references corresponding to entities, and determining, from the unstructured text data, attributes associated with the entities. The method also includes obtaining structured data including predefined attributes associated with the entities, and comparing attributes associated with a first coreference unit with attributes associated with a second coreference unit. The first coreference unit is a sub-entity representation having the attributes determined from the unstructured text data and the second coreference unit is a sub-entity representation having the predefined attributes. The method further includes determining, based on the comparison, whether the first coreference unit and the second coreference unit both correspond to the same entity.

Systems and methods for entity resolution using attributes from structured and unstructured data

Systems and methods for coreference resolution are disclosed. In one embodiment, a method includes locating, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain. The method also includes determining an entity category for each respective one of the plurality of chains and determining one or more entity attributes from structured data and unstructured data. The method further includes, based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a Zipfian-like distribution having a head region and a tail region.

Systems and methods for large scale global entity resolution

According to one aspect, a computer-implemented method for entity resolution is disclosed. In one embodiment, the method includes generating a semantic hash for an entity having an assigned entity identifier (ID) and, upon the occurrence of an entity milestone, changing the entity ID. The method further includes generating a semantic hash for the entity having the changed entity ID, and maintaining history information associated with the entity and corresponding entity IDs and semantic hashes over a period of time that includes a plurality of entity milestones. The method also includes periodically removing at least one set of older entities and retaining entity IDs and semantic hashes associated with the removed entities.

Semantic hashing in entity resolution

According to one aspect, a method for coreference resolution is provided. In one embodiment, the method includes receiving a segment of text that includes mentions corresponding to entities. A first feature vector is generated based on one or more features associated with a first mention, and a second feature vector is generated based on based on one or more features associated with a second mention. A measure of similarity between the first feature vector and second feature vector is computed and, based on the computed measure of similarity, it is determined if the first mention and the second mention both correspond to the same entity.

System and method for coreference resolution

A stockbutt system for rifles to abate shock during the firing of a rifle is disclosed, having a butt at the near end. The system includes a rifle and an insert with the butt having a near most first end in a generally planar configuration perpendicular to the axis of the barrel. The first end of the butt has a concave configuration when viewed from the side and a teardrop configuration when viewed from the end. The teardrop shape includes an upper semicircular curve at the top with a diameter essentially equal to the diameter of the widest portion of the butt. The teardrop shape further includes downwardly tapering side edges terminating in a U-shaped configuration at the bottom. The lower semicircular curve has a diameter less than the upper semicircular curve. The insert has an essentially flat far most face in its size and shape to correspond to the rearmost face of the butt. The insert is provided being fabricated of an elastomeric material to abate vibrations during the firing of a rifle. A coupling component couples the far most face of the insert and the rearmost face of the butt.

Stockbutt system

An air bag and steering lock device including a housing. The housing has a top half and a bottom half that allows the housing to be positioned around a column of a steering wheel for replacing the covering of the column. A J-bar member is provided. The J-bar has a back bar with a pair of lateral extents projecting in a forward direction. One of the lateral extents has an interior side with a plurality of catch slots adjacent an end. Lastly, a locking means is fixedly attached to the top surface of the top half of the housing. The locking means is capable of receiving the one lateral extent of the J-bar for locking the J-bar over the steering wheel to limit the steering wheel's movement and disassembly.

Growing community of inventors

Nashville, TN, United States of America

Kenneth Loran Graham