About

Jeu-Hee Hahn, MD, is an Assistant Professor of Clinical Psychiatry at the University of Pennsylvania's Perelman School of Medicine. She serves as an Attending Physician at the Children's Hospital of Philadelphia and is the Administrative Lead Psychiatrist for the Psychiatry Resident Clinic at CHOP. Dr. Hahn specializes in clinical psychiatry with a focus on patient care and psychiatric consultation services. Her educational background includes a Bachelor of Science in Biological Sciences with a concentration in Organismal Biology and Physiology from Drexel University in 2012, and an MD from Drexel University College of Medicine in 2016. Her professional roles involve leading psychiatric services and contributing to the clinical and educational missions of the institution.

Research topics

• Computer science
• World Wide Web
• Multimedia
• Business
• Information retrieval

Selected publications

• A Comparative Evaluation of the Share-VDE Search System

  Cataloging & Classification Quarterly · 2024-05-18

  article1st authorCorresponding

  The Share-VDE search system (https://svde.org) shifts the library discovery paradigm from record-based indexing and retrieval to that of linked data entity exploration. This paper reports results of iterative testing of multiple versions of the Share-VDE interface. The testing included remote user experience (UX) interviews with a total of twenty participants across four rounds of tests spanning two years. The comparison among participants encompassed catalogers, students of all levels, and faculty. Synthesizing IFLA LRM user tasks with interface evaluation methods supported the qualitative inquiry into how linked data systems in general, and BIBFRAME specifically, can support search system objectives.

  PublisherDOI

• Bifurcation of Semi-Automated Subject Indexing Services

  Library Resources and Technical Services · 2024-01-01

  articleOpen access1st authorCorresponding

  Semi-automated subject indexing methods use attributes from metadata descriptions as training data. A survey to shape inclusion of metadata attributes that align a machine learning model within a contextual linguistic domain generated the initial genre targets for experimentation. The second part of this study then tested the genre attributes from the survey. These bifurcations (or branching points) served as the basis for machine learning model development and evaluation. The machine learning models in semi-automated indexing systems are the drivers of the automated subject outputs. The initial results of this multipart experiment indicate that measures of the mean precision and recall (the F1 metric) improved for several—but not all—types of genres that were of interest to knowledge workers.

  PublisherOA PDFDOI

• The Share-VDE ontology: a BIBFRAME extension for linked data discovery

  Zenodo (CERN European Organization for Nuclear Research) · 2023-09-10 · 3 citations

  reportOpen access1st authorCorresponding

  The Share-VDE ontology is an extension to BIBFRAME. While the ontology supports the discovery functionality of Share-VDE and the Share family search systems, it may be re-used in any system requiring a bridge among BIBFRAME, IFLA LRM and RDA. Classes of the Share-VDE ontology include the svde:Opus, svde:OpusType, and svde:Work. The Share-VDE ontology achieves interoperability among the major bibliographic models by asserting that bibliographic entities are described by attribute sets. The attribute set modeling approach is a departure from the conceptual modeling that has informed the development of nearly all modern linked data models.

  PublisherDOI

• The Share-VDE ontology: a BIBFRAME extension for linked data discovery

  Zenodo (CERN European Organization for Nuclear Research) · 2023-09-10

  reportOpen access1st authorCorresponding

  The Share-VDE ontology is an extension to BIBFRAME. While the ontology supports the discovery functionality of Share-VDE and the Share family search systems, it may be re-used in any system requiring a bridge among BIBFRAME, IFLA LRM and RDA. Classes of the Share-VDE ontology include the svde:Opus, svde:OpusType, and svde:Work. The Share-VDE ontology achieves interoperability among the major bibliographic models by asserting that bibliographic entities are described by attribute sets. The attribute set modeling approach is a departure from the conceptual modeling that has informed the development of nearly all modern linked data models.

  PublisherDOI

• Guest editorial: Anti-racist scholarship and practice in library and information science

  Reference Services Review · 2022-02-28

  editorialOpen accessSenior author
  PublisherOA PDFDOI

• Semi-Automated Methods for BIBFRAME Work Entity Description

  Cataloging & Classification Quarterly · 2021-11-17 · 3 citations

  articleOpen access1st authorCorresponding

  This paper reports an investigation of machine learning methods for the semi-automated creation of a BIBFRAME Work entity description within the RDF linked data editor Sinopia (https://sinopia.io). The automated subject indexing software Annif was configured with the Library of Congress Subject Headings (LCSH) vocabulary from the Linked Data Service at https://id.loc.gov/. The training corpus was comprised of 9.3 million titles and LCSH linked data references from the IvyPlus POD project (https://pod.stanford.edu/) and from Share-VDE (https://wiki.share-vde.org). Semi-automated processes were explored to support and extend, not replace, professional expertise.

  PublisherOA PDFDOI

• Health Care-Related Expiring Provisions of the 117th Congress, First Session [June 14, 2021]

  Library of Congress. Congressional Research Service · 2021-06-14

  article
  Publisher

• COVID-19 Vaccine: Financing for Its Administration

  2021-02-19

  article
  Publisher

• Medicare Accelerated and Advance Payments and COVID-19: Frequently Asked Questions [March 1, 2021]

  Library of Congress. Congressional Research Service · 2021-03-01

  article1st authorCorresponding
  Publisher

• Report of the ALA Core Catalog Form and Function Interest Group during Core Virtual Interest Group Week, February 5, 2021

  Technical Services Quarterly · 2021-10-02

  article
  PublisherDOI

Frequent coauthors

• David Ward

  University of Illinois Urbana-Champaign

  10 shared

• Lori S. Mestre

  10 shared

• Christopher M. Davis

  University of Oxford

  6 shared

• Paulette C. Morgan

  5 shared

• Cliff Binder

  5 shared

• Marco A. Villagrana

  5 shared

• Patricia A. Davis

  Children's Mercy Hospital

  4 shared

• Edward C. Liu

  4 shared

Labs

• Jeu-Hee Hahn LaboratoryPI

Education

• Doctor of Philosophy - PhD (in progress), Information Sciences

  University of Illinois at Urbana-Champaign

  2026

• Certificate of Advanced Study, Library and Information Science

  University of Illinois at Urbana-Champaign

  2011

• M.S. Library and Information Science, Library and Information Science

  University of Illinois at Urbana-Champaign

  2007