Digital Reasoning Systems, Inc.

Vishnuvardhan Balluru

Kenneth Loran Graham

John Wagster

Keith Ellis Massey

Robert Metcalf

Sarah Cannon

Adam Jaggers

Bill Dipietro

Naomi Hilliard

Phillip Daniel Michalak

James Johnson 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

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 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

Growing community of inventors

Franklin, TN, United States of America

Vishnuvardhan Balluru