At&t Intellectual Property I, L.p.

At+t Corp.

New Jersey Institute of Technology

Guy Jacobson

Divesh Srivastava

Balachander Krishnamurthy

Colin Goodall

Simon Tse

Wen-Ling Hsu

Richard Drechsler

Manoop Talasila

John Mark F Mocenigo

Mazin E Gilbert

John F Murray

Syed Anwar Aftab

Dan Suciu

Ann Eileen Skudlark

Rittwik Jana

Tan Xu

Reuben Klein

John Mark Mocenigo

Sylvia Halasz

John Grothendieck

Kazi Farooqui

Anwar Syed Aftab

Jeremy Huntley Greet Wright

Cristian Borcea

Bradley Keith Mohs

Xiaopeng Jiang

Ritu Kumar

Thomas Paul Ventimiglia

Greg B Kinne

Arnold Lent

Yi Chen

Shuai Zhao

Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.

Synchronization of artificial intelligence based microservices

An artificial intelligence (AI) automation to improve network quality based on predicted locations is provided. A method can include training, by a first device comprising a processor and according to model configuration parameters received from a second device that is not the first device, a local machine learning model with training data derived from first location data collected by the first device; transmitting, by the first device to the second device, anonymized model features associated with the local machine learning model; in response to the transmitting of the anonymized model features, receiving, by the first device from the second device, an aggregated machine learning model; and estimating, by the first device, a future position of the first device by applying the aggregated machine learning model to second location data collected by the first device.

Artificial intelligence automation to improve network quality based on predicted locations

A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.

Network-based machine learning microservice platform

Systems and methods mediate anomaly notifications in health data to health alerts using data structures and logic to organize, contain, and dispose of identified health anomalies. Multiple detection algorithms, operating asynchronously and independently, run against one or more health data streams. Examples of data streams are electronic laboratory requisitions and results, OTC sales of medicines and medical supplies, emergency department visit data, and others. The outputs of anomaly detection generators&#x2014;anomaly notifications (anomalies)&#x2014;are processed by the invention. The case manager organizes anomaly notifications and supports collaborative decision making and disposition among expert users.

Biosurveillance notifications

In one example, the present disclosure describes a device, computer-readable medium, and method for sentiment analysis tuning. In one example, the method, includes acquiring a first sentiment analysis-generated score for a first string of text, wherein the first string of text includes a first plurality of words, and wherein the first sentiment analysis-generated score is calculated using a set of first values associated with the first plurality of words, calculating a second value for at least one word of the first plurality of words, based on a non-sentiment-analysis generated score associated with the first string of text, acquiring a second string of text, wherein the second string of text includes a second plurality of words, and wherein the second plurality of words includes the at least one word, and calculating a sentiment analysis-generated score for the second string of text, using the second value for the at least one word.

Sentiment analysis tuning

A system and method for mediating anomaly notifications in health data to health alerts using data structures and logic to organize, contain, and disposition identified health anomalies. Multiple generators of anomaly notifications operating asynchronously and independently can be processed. The case manager organizes anomaly notifications and supports collaborative decision making among users with diverse areas of expertise. A network server stores health data that has been gathered from various sources. A user can visualize the data on a client computer networked to the server by downloading from the server user specified sets of health-related data based on a case or set of anomalies describing a subset of the data, and source code for visualizing the data.

Tool for visual exploration of medical data

A system and method for mediating anomaly notifications in health data to health alerts using data structures and logic to organize, contain, and disposition identified health anomalies. Multiple generators of anomaly notifications operating asynchronously and independently can be processed. The case manager organizes anomaly notifications and supports collaborative decision making among users with diverse areas of expertise.

Case management system and method for mediating anomaly notifications in health data to health alerts

Systems and methods are provided to evaluate a search engine using search results retrieved from a plurality of different search engines. For example, a controller can randomly distribute a set of pre-formulated queries to a plurality of computers to query the search engines at random times to obtain search results and combine the search results to evaluate the completeness of a query result provided by a particular search engine. The controller may simulate the random queries from users using a set of computers and may reduce the burden on the search engines by spreading out the query activities over a period of time, such as a month.

Systems and methods to evaluate search qualities

A method, an apparatus, and a computer-readable medium are provided. Whether at least one significant change occurs in a use of at least one word of a group of text documents of a text corpus is determined. A display based, at least in part, on at least one change point corresponding to the at least one significant change is presented when the at least one significant change is determined to have occurred.

Method and apparatus for automatic detection and visualization of changes within large streams of text

A system, a method, an apparatus, and a computer-readable medium are provided. Co-occurrences of words or terms in a group of text documents are determined. A score for each of the co-occurrences of words or terms is calculated. A graphic view is presented. The graphic view has nodes that include at least one word or term and edges that join at least two nodes and depict a relationship among the at least two nodes. A layout of the graphic view includes a minimum number of crossings of the edges.

Method and apparatus for large volume text summary and visualization

Disclosed herein is a multi-domain anomaly pattern definition and detection module. The module receives raw data from different kinds of anomalies from a variety of detection algorithms and generates scores associated with the data. If one or more scores exceed a threshold, then the algorithm gathers further information which may include counts or listings of detailed data for a geographic region which may include such information as emergency department and lab department data related to a particular health concern such as a respiratory syndrome. Summaries are provided which may identify anomalies and numbers of events according to geographic region and utilizing probability algorithms. Other databases such as animal data collected under the Department of Agriculture may also be utilized. The data is presented in a familiar form such as a map or a table such that a subject matter expert may determine whether to further investigate an anomaly as a potential risk, for example, a health risk.

Method and apparatus for multi-domain anomaly pattern definition and detection

A method more efficiently indexes dynamic documents. The method adjusts the frequency with which dynamic documents are retrieved taking into account the extent to which the document varies between its most recent retrievals. Furthermore, the method selects portions of the document to be indexed based on the substance of the differences between recently retrieved copies.

Growing community of inventors

Bridgewater, NJ, United States of America

Guy Jacobson