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Ein Kapitel aus dem Buch Archives, Access and Artificial Intelligence

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"Authors (by order of appearance in the volume)". Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections, edited by Lise Jaillant, Bielefeld: Bielefeld University Press, 2022, pp. 219-224. https://doi.org/10.1515/9783839455845-010

(2022). Authors (by order of appearance in the volume). In L. Jaillant (Ed.), Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections (pp. 219-224). Bielefeld: Bielefeld University Press. https://doi.org/10.1515/9783839455845-010

2022. Authors (by order of appearance in the volume). In: Jaillant, L. ed. Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections. Bielefeld: Bielefeld University Press, pp. 219-224. https://doi.org/10.1515/9783839455845-010

"Authors (by order of appearance in the volume)" In Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections edited by Lise Jaillant, 219-224. Bielefeld: Bielefeld University Press, 2022. https://doi.org/10.1515/9783839455845-010

Authors (by order of appearance in the volume). In: Jaillant L (ed.) Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections. Bielefeld: Bielefeld University Press; 2022. p.219-224. https://doi.org/10.1515/9783839455845-010

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Kapitel in diesem Buch

Frontmatter 1
Contents 5
Introduction 7
Chapter 1: Artificial Intelligence and Discovering the Digitized Photoarchive 29
Chapter 2: Web Archives and the Problem of Access: Prototyping a Researcher Dashboard for the UK Government Web Archive 61
Chapter 3: Design Thinking, UX and Born-digital Archives: Solving the Problem of Dark Archives Closed to Users 83
Chapter 4: Towards Critically Addressable Data for Digital Library User Studies 109
Chapter 5: Reviewing the Reviewers: Training Neural Networks to Read Peer Review Reports 131
Chapter 6: Supervised and Unsupervised: Approaches to Machine Learning for Textual Entities 157
Chapter 7: Inviting AI into the Archives: The Reception of Handwritten Recognition Technology into Historical Manuscript Transcription 179
AFTERWORD: Towards a new Discipline of Computational Archival Science (CAS) 205
Authors (by order of appearance in the volume) 219

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https://doi.org/10.1515/9783839455845-010

Kapitel in diesem Buch

Frontmatter 1
Contents 5
Introduction 7
Chapter 1: Artificial Intelligence and Discovering the Digitized Photoarchive 29
Chapter 2: Web Archives and the Problem of Access: Prototyping a Researcher Dashboard for the UK Government Web Archive 61
Chapter 3: Design Thinking, UX and Born-digital Archives: Solving the Problem of Dark Archives Closed to Users 83
Chapter 4: Towards Critically Addressable Data for Digital Library User Studies 109
Chapter 5: Reviewing the Reviewers: Training Neural Networks to Read Peer Review Reports 131
Chapter 6: Supervised and Unsupervised: Approaches to Machine Learning for Textual Entities 157
Chapter 7: Inviting AI into the Archives: The Reception of Handwritten Recognition Technology into Historical Manuscript Transcription 179
AFTERWORD: Towards a new Discipline of Computational Archival Science (CAS) 205
Authors (by order of appearance in the volume) 219

Authors (by order of appearance in the volume)

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