Performance-based evolution of content annotation taxonomies

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) dat...

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Bibliographic Details
Main Authors Farre Guiu, Miquel Angel, Pernias, Pablo, Lucien, Mara Idai, Porta Valles, Marcel, Alfaro Vendrell, Monica, Martin, Marc Junyet, Accardo, Anthony M, Ovanessian, Melina
Format Patent
LanguageEnglish
Published 29.08.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
ELECTROTHERAPY
HUMAN NECESSITIES
HYGIENE
MAGNETOTHERAPY
MEDICAL OR VETERINARY SCIENCE
PHYSICS
RADIATION THERAPY
ULTRASOUND THERAPY
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Summary: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.
Bibliography:Application Number: US202117396460