Disney Enterprises, Inc.

Melina Ovanessian

Anthony M Accardo

Miquel Angel Farre Guiu

Monica Alfaro Vendrell

Pablo Pernias

Mara Idai Lucien

Marc Junyet Martin

Marcel Porta Valles

According to one implementation, a system includes a computing platform having processing hardware, a system memory storing a software code; and a machine learning model based classifier. The processing hardware is configured to execute the software code to receive tagging quality assurance (QA) data including multiple terms applied as tags and corrections to those tags, to identify, using the tagging QA data, a first problematic term, and to classify, using the machine learning model based classifier, the first problematic term as one of confusing or flawed. The processing hardware is further configured to execute the software code to obtain, when the first problematic term is classified as confusing, a comparative sample for clarifying use of the first problematic term, and to obtain, when the first problematic term is classified as flawed, modification data for editing a predetermined annotation taxonomy including the first problematic term.

Performance-based evolution of content annotation taxonomies

Growing community of inventors

La Crescenta, CA, United States of America

Melina Ovanessian