Zendesk, Inc.

Arwen Twinkle E Griffioen

Anh Thien Dinh

Soon-Ee Cheah

Michael G Mortimer

Wai Chee Yau

Christopher J Hausler

Sean D Caffery

Jeffrey P Theobald

Damen Turnbull

Vivek Chopra

David S Liberman

J David Niergarth

Thomas Pelletier

Jason Edward Maynard

Lisa Friedman

Hao Sun

Arvind Kunday Anantharaman

Srikanth Veeraraghavan

Indika D Jayasinghe

Bob Dharmendra Raman

The disclosed embodiments relate to a system that detects and controls operations performed by abusive accounts in a customer-relationship-management system. During operation, the system obtains account-related information for an account in the customer-relationship-management system. Next, the system determines a likelihood that the account is being used for abusive purposes based on the account-related information. Finally, the system limits a rate of processing for application-programming interface (API) calls made from the account to the customer-relationship-management system based on the determined likelihood that the account is being used for abusive purposes.

Rate-limiting API calls for an account in a customer-relationship-management system based on predicted abusive behavior

The disclosed embodiments relate to a system that suggests helpful articles to resolve a customer request. During operation, the system receives the customer request, wherein the customer request is associated with a product or a service used by the customer. Next, the system feeds a set of words from the customer request through a model to generate a request vector comprising numerical values representing words in the customer request. The system then compares the request vector against article vectors representing articles in a set of help center articles to determine whether the customer request matches one or more help center articles. If the customer request matches one or more help center articles, the system presents the one or more help center articles to the customer to facilitate automatically resolving the customer request.

Article-suggestion system for automatically resolving customer-service requests

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Montmorency, Australia

Arwen Twinkle E Griffioen