Making Text Analytics More Approachable: An Example Using a Customer Service Application

Описание: Text analytics proves to be most effective when it is approachable to business users, packaged within easily deployable and accessible applications, and helps business users make better and effective decisions. Core text analytics capabilities help analysts and data scientists categorize documents, extract information, discover topics and identify sentiment. In this presentation, we take an application for customer service as an example, use recently added functionality that publishes text analytics models to API endpoints, and demonstrate how consumers of AI can make decisions, obtain recommendations and gain insights through reports. This presentation helps demonstrate how SAS is making is easier for users and organizations to make decisions and gain value from text analytics.

PRESENTER: Sundaresh Sankaran, Solutions Architect, SAS
TOPIC: Text Analytics

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