Accenture Global Solutions Limited

Accenture Global Services Gmbh

Christopher Yen-Chu Chan

Lan Guan

John D Bolze

Guanglei Xiong

Sukryool Kang

Anwitha Paruchuri

Jayashree Subrahmonia

Louise Noreen Barrere

Thomas Kim

Ivan A Wong

Wenxian Zhang

William L Gewirtz

Danielle Moffat

Sundaravadivelan Ramamoorthy

Aiperi Iusupova

Saurabh Mathur

Stephen M Dadoly

Nivedita Samal

Soumya Singh

Jing Su Brewer

Aaron James Sander

Paul J Bultema

John A Morgan

Implementations are directed to receiving a set of tuples, each tuple including an entity and a product from a set of products, for each tuple: generating, by an embedding module, a total latent vector as input to a recommender network, the total latent vector generated based on a structural vector, a textual vector, and a categorical vector, each generated based on a product profile of a respective product and an entity profile of the entity, generating, by a context integration module, a latent context vector based on a context vector representative of a context of the entity, and inputting the total latent vector and the latent context vector to the recommender network, the recommender network being trained by few-shot learning using a multi-task loss function, and generating, by the recommender network, a prediction including a set of recommendations specific to the entity.

Few-shot learning for multi-task recommendation systems

Implementations of the present disclosure include receiving a goal, providing a problem-specific knowledge graph that is responsive to at least a portion of the goal, determining a set of events from the problem-specific knowledge graph, processing data representative of events in the set of events through a first machine learning (ML) model to provide a set of event scores, each event score in the set of event scores being associated with a respective event in the set of events, determining a sub-set of events based on the set of event scores, for each event in the sub-set of events, determining at least one action by processing a sequence of actions through a second ML model, and outputting the sub-set of events and a set of actions for execution of at least one action in the set of actions.

Early pattern detection in data for improved enterprise operations

A digital content communication system for account management and predictive analytics may be provided. The system may include an analytics system that communicates with one or more servers and one or more data stores to provide digital content management in a network. The analytics system may include a data access interface to receive data associated with a customer, as well as a processor to: standardize the received data using a standardization technique; process the standardized data using a dark data processing technique; generate a customer fit score and a digital density score based on the dark data processing of the standardized data; match received data associated with a customer against at least one variable using at least one matching technique; create a lead analytical record (LAR); prioritize leads in the LAR using a predictive modeling technique; and establish optimized channel assignment based on at least one of the customer fit score, the digital intensity score, the LAR, or the matching and prioritization actions.

Digital content prioritization to accelerate hyper-targeting

A customized content selection and delivery system is operable to create a customized content channel package for a subscriber and customized content channel package to a customer premises over a content delivery network. A multi-level analysis based on measured content consumption metrics is performed to select content provider channels for the customized content channel package.

Customized content channel generation and delivery for service providers

A service provider network migration system migrate services from a first network infrastructure to a second network infrastructure. A joined circuits dataset is created that associates circuits in the first network infrastructure with a service provided by the circuit and a customer receiving the service via the first network infrastructure. A product mappings dataset is created that maps each service in the first network infrastructure to at least one target service to be provided in the second network infrastructure. A migration sequencing server creates a migration plan according to the information in the datasets, and forecasts for customer migration rate and revenue generation for the target services are estimated. A provisioning server configures parameters for the circuits in the second network infrastructure via a network according to the migration plan to deploy the target services in the second network infrastructure.

Service provider network migration

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Jersey City, NJ, United States of America

Christopher Yen-Chu Chan