<?xml version="1.0" encoding="UTF-8"?><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>ai-assisted-metadata-extraction-for-institutional-repository-submissions-2024-015</dc:title><dc:creator>Chioma Lawal</dc:creator><dc:date>2024</dc:date><dc:description>This study designs and evaluates an AI assisted metadata extraction workflow for institutional repository submissions, focusing on title parsing, author validation, keyword generation, and librarian review accuracy. The work demonstrates how automated suggestions can reduce cataloguing time while preserving human oversight and metadata quality.</dc:description><dc:identifier>https://inrepscholar.com/projects/894</dc:identifier></oai_dc:dc>