Automatically Detecting References from the Scholarly Literature to Records in Archives

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Scholars use references in books and articles to materials found in archives as one way of finding those materials, but present systems for archival access do not exploit that information. To change that, the first step is to find archival references in the scholarly literature; that is the focus of this paper. Several classifier designs are compared using a few thousand manually annotated footnotes and endnotes assembled from a large set of open access papers on history. The results indicate that fairly high recall and precision can be achieved.

Original languageEnglish
Title of host publicationLeveraging Generative Intelligence in Digital Libraries
Subtitle of host publicationTowards Human-Machine Collaboration - 25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023, Proceedings
EditorsDion H. Goh, Shu-Jiun Chen, Suppawong Tuarob
PublisherSpringer Science and Business Media Deutschland GmbH
Pages100-107
Number of pages8
ISBN (Print)9789819980871
DOIs
Publication statusPublished - 2023
Event25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023 - Taipei, Taiwan, Province of China
Duration: Dec 4 2023Dec 7 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14458 LNNS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period12/4/2312/7/23

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Automatically Detecting References from the Scholarly Literature to Records in Archives'. Together they form a unique fingerprint.

Cite this