Other

Capital One Services, LLC

Francisco Gutierrez

Herbert Willi Artur Ristock

Nikolay I Korolev

Andriy Vladimirovich Ryabchun

Conor McGann

Josef Eric Eisner

Gordon L Bell

Bharath Aravamudhan

Anand Pai Krishnanand Nitin

Bohdan Klepar

Eiran Shalev

Sandeep Narayanaswami

Matthew Tomaszewicz

Stanislav Lypchanskyy

Stanislav Lypachanskyy

A system, method, and computer-readable medium for generating factual and/or counterfactual data are described. This may have the effect of improving the complexity of data available for training machine learning models. The models may include agent-based models (ABMs) in which the agent definitions are decoupled from the simulation. In one or more aspects, some agents may have attributes and associated behaviors that permit them to be reused in different ABMs to simulate different systems.

Extensible agents in agent-based generative models

A system, method, and computer-readable medium for generating factual and/or counterfactual data are described. This may have the effect of improving the complexity of data available for training machine learning models. The models may include, but not limited to, a probabilistic graphical model (PGM) and/or an agent-based model (ABM). Further aspects may provide for scrubbing actual data to create a data model that does not reveal the content of the underlying source data. Yet further aspects may provide for validating a data model.

Generation of synthetic data using agent-based simulations

A system and method for making engagement offers. A processor monitors a navigation path of a user navigating a website. The processor makes an offer for engagement with the user on a first web page reached by the user upon following the navigation path. The processor monitors a reaction of the user to the offer for engagement, and updates tag data associated with a second web page encountered by the user while traversing the navigation path. The tag data is updated based on the reaction of the user to the offer for engagement.

System and method for making engagement offers based on observed navigation path

A system and method for proactively making knowledge offers. A processor is configured to gather information on interactions by a user with resources provided by an enterprise having a customer contact center. The processor anticipates need of the user based on the gathered information, and generates a query based on the anticipated need. Prior to the user expressly requesting knowledge relating to a particular topic, the processor proactively identifies and suggests the knowledge to the user based on the generated query. The processor receives feedback relating to the suggested knowledge and outputs based on the feedback, a relevance score for the suggested knowledge.

Proactive knowledge offering system and method

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San Francisco, CA, United States of America

Francisco Gutierrez