Archives, Access and Artificial Intelligence

Archives, Access and Artificial Intelligence

Digital archives are transforming the Humanities and the Sciences. Digitised collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digita...

Descripción completa

Detalles Bibliográficos
Autor Corporativo: Loughborough University funder (funder)
Otros Autores: Jaillant, Lise, author (author), Bell, Mark, contributor (contributor), Donoho, David L., contributor (editor), Eve, Martin Paul, contributor, Gadie, Robert, contributor, Gooding, Paul, contributor, Han, X.Y., contributor, Hodel, Tobias, contributor, Jaillant, Lise, contributor, Jaillant, Lise, editor, Johnson, C. Richard, contributor, Marciano, Richard, contributor, Odeniyi, Victoria, contributor, Papyan, Vardan, contributor, Parvin, Shahina, contributor, Prokop, Ellen, contributor, Storrar, Tom, contributor, Terras, Melissa, contributor, Winters, Jane, contributor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Bielefeld : Bielefeld University Press 2022.
Colección:Digital humanities research.
Materias:
Digital libraries > Access control.
Artificial intelligence > Library applications.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009794908706719
Tabla de Contenidos:
  • Frontmatter
  • Contents
  • Introduction
  • Chapter 1: Artificial Intelligence and Discovering the Digitized Photoarchive
  • Chapter 2: Web Archives and the Problem of Access: Prototyping a Researcher Dashboard for the UK Government Web Archive
  • Chapter 3: Design Thinking, UX and Born-digital Archives: Solving the Problem of Dark Archives Closed to Users
  • Chapter 4: Towards Critically Addressable Data for Digital Library User Studies
  • Chapter 5: Reviewing the Reviewers: Training Neural Networks to Read Peer Review Reports
  • Chapter 6: Supervised and Unsupervised: Approaches to Machine Learning for Textual Entities
  • Chapter 7: Inviting AI into the Archives: The Reception of Handwritten Recognition Technology into Historical Manuscript Transcription
  • AFTERWORD: Towards a new Discipline of Computational Archival Science (CAS)
  • Authors (by order of appearance in the volume)

Ejemplares similares