Core Copy Cataloging Interest Group

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last person joined: 22 days ago 

✉ Send an email to ALA-CoreCopyCataloging@ConnectedCommunity.org to start a discussion or share a file.

About this Group

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Purpose: Discusses informally common problems concerning copy cataloging, including discussions on quality control of copy cataloging units, workflows in copy cataloging, copy cataloging of all kinds of materials (monographs, serials, audiovisuals, etc.), staffing needs in copy cataloging, training of copy cataloging, effects of changes in cataloging standards, and technology on copy cataloging.

This interest group is part of Core's Metadata and Collections Section.

Portraits of three Core members with caption Become a Member: Find Your Home: Core.

 

Register now! ACRL TSIG program on AI, NLP, BERT, and subject indexing

  • 1.  Register now! ACRL TSIG program on AI, NLP, BERT, and subject indexing

    Posted Mar 08, 2024 12:48 PM

    The ACRL Technical Services Interest Group invites interested parties to attend a virtual program on AI, NLP, BERT, and assisted subject indexing (details below). The program will take place Wednesday, March 20, 2024, 1:00-2:00 pm (Eastern). There is no cost to attend, but registration is required. Register using this link:

    Welcome! You are invited to join a meeting: An Analysis of BERT (NLP) for Assisted Subject Indexing for Digital Library Collections: A Dialogue Between Library Metadata and Data Science. After registering, you will receive a confirmation email about joining the meeting.

    Speaker: Charlene Chou, Head of Knowledge Access, New York University, Division of Libraries

    Presentation title: An Analysis of BERT (NLP) for Assisted Subject Indexing for Digital Library Collections: A Dialogue Between Library Metadata and Data Science

    Abstract: Subject indexing has been one of users' top demands for accessing library resources effectively. With the rapid increase of digital resources, automated subject indexing has been an important research subject in recent years. However, there are major challenges for providing quality subject access to users and automatic subject indexing solutions have still not been widely adopted in the discovery systems of libraries and related institutions, according to various studies.

    In light of AI (Artificial Intelligence) and NLP (Natural language processing) technologies, this presentation examines the feasibility of using AI/NLP models to enhance the subject indexing of digital resources. While BERT (Bidirectional Encoder Representations from Transformers) models are widely used in scholarly communities, we assess whether BERT models can be used in machine-assisted indexing in the Project Gutenberg collection, through suggesting Library of Congress subject headings filtered by certain Library of Congress Classification subclass labels. The findings of this study are informative for further research on BERT models to assist with automatic subject indexing for digital library collections.

    A Q&A session will follow the speaker's presentation.

    Thank you,
    Dan Tam Do (ACRL TSIG Convener)
    Alyssa Koclanes (ACRL TSIG Incoming Convener)



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    Dan Tam Do
    Head of Cataloging
    University of Pittsburgh
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