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Full-Text Articles in Library and Information Science
News – Digital Library Of Georgia, Mandy L. Mastrovita
News – Digital Library Of Georgia, Mandy L. Mastrovita
Georgia Library Quarterly
No abstract provided.
Spark A Conversation On Metadata Inclusiveness, Sai Deng
Spark A Conversation On Metadata Inclusiveness, Sai Deng
Faculty Scholarship and Creative Works
This session introduces the context for metadata inclusiveness and presents some of the efforts the speaker has been involved with, including helped create the Inclusive Metadata & Conscious Editing Resources List as a member of the Sunshine State Digital Network (SSDN) Metadata Working Group, and organized “Embracing Equity, Diversity and Inclusion (EDI) in Library Cataloging” for the ALA Core Interest Group Week in Spring 2021. It focuses on describing cases, examples and other resources from the SSDN Resources List, so as to give librarians and staff members in Technical Services at the University Central Florida Libraries a better understanding and …
Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations, Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox
Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations, Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox
Computer Science Faculty Publications
Electronic Theses and Dissertations (ETDs) contain domain knowledge that can be used for many digital library tasks, such as analyzing citation networks and predicting research trends. Automatic metadata extraction is important to build scalable digital library search engines. Most existing methods are designed for born-digital documents, so they often fail to extract metadata from scanned documents such as ETDs. Traditional sequence tagging methods mainly rely on text-based features. In this paper, we propose a conditional random field (CRF) model that combines text-based and visual features. To verify the robustness of our model, we extended an existing corpus and created a …