Verizon Patent and Licensing Inc.

Srinivasan Krishnamurthy

Vipul Jha

Safwan Aly

Harish Babu Arunachalam

Rajat Sharma

Senthil Muthusamy

Travis R McLaren

Pritam Bedse

Sailesh K Mishra

Rishi Kanth Chitti

Philip A Jenkins

Venkateswararao Godavarti Veera

John Benjamin Lertola

Khagender Arrekuti

Vinod Khanna Saini Ganesh

Pavani Kamalapuram

Richard J Worthington

John Russo

A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

Systems and methods for profiling and clustering network-connected devices

A device may receive, from a customer platform, customer event data identifying events occurring between customers and an entity, and may receive, from the customer platform, customer action data generated by machine learning models and identifying customer actions to be taken by the customer platform in response to the occurrence of the events. The device may receive, from the customer platform, customer results data identifying results of the customer actions taken by the customer platform, and may calculate current key performance indicators based on the customer event data, the customer action data, and the customer results data. The device may retrain one or more of the machine learning models based on the current key performance indicators to generate one or more retrained machine learning models, and may provide the one or more retrained machine learning models to the customer platform.

Systems and methods for measuring and validating key performance indicators generated by machine learning models

A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' affinity with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

A platform can receive information regarding a user interaction, wherein the user interaction is associated with one or more channels that correspond to respective interfaces or media for the user interaction; retrieve supplemental information associated with the user interaction, wherein the supplemental information relates to at least one of: a state of a managed device associated with the user interaction, or a previous user interaction; identify, based on the information regarding the user interaction or the one or more channels, one or more models to process the information regarding the user interaction and the supplemental information, wherein the one or more models are identified from a plurality of models; determine, using the one or more models, an action to be performed with regard to the user interaction; and provide information identifying the action.

Interpretation of user interaction using model platform

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Irving, TX, United States of America

Srinivasan Krishnamurthy