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dc.contributor.authorNanetti, Andrea
dc.date.accessioned2025-03-07T21:33:48Z
dc.date.available2025-03-07T21:33:48Z
dc.date.issued2023
dc.date.submitted2023-08-31T08:42:20Z
dc.identifierONIX_20230831_9781000802078_23
dc.identifierOCN: 1331300127
dc.identifierhttps://library.oapen.org/handle/20.500.12657/75951
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/167667
dc.description.abstractNanetti outlines a methodology for deploying artificial intelligence and machine learning to enhance historical research. Historical events are the treasure of human experiences, the heritage that societies have used to remain resilient and express their identities. Nanetti has created and developed an interdisciplinary methodology supported by practice-based research that serves as a pathway between historical and computer sciences to design and build computational structures that analyse how societies create narratives about historical events. This consilience pathway aims to make historical memory machine-understandable. It turns history into a computational discipline through an interdisciplinary blend of philological accuracy, historical scholarship, history-based media projects, and computational tools. Nanetti presents the theory behind this methodology from a humanities perspective and discusses its practical application in user interface and experience. An essential read for historians and scholars working in the digital humanities.
dc.languageEnglish
dc.rightsopen access
dc.subject.otherHistory
dc.subject.otherGeneral and world history
dc.titleComputational Engineering of Historical Memories
dc.title.alternativeWith a Showcase on Afro-Eurasia (ca 1100-1500 CE)
dc.typebook
oapen.identifier.doi10.4324/9781003310860
oapen.relation.isPublishedByfa69b019-f4ee-4979-8d42-c6b6c476b5f0
oapen.relation.isFundedBye409757c-996d-49d4-9964-b3091fe3d39b
oapen.relation.isbn9781000802078
oapen.relation.isbn9781032316802
oapen.relation.isbn9781003310860
oapen.relation.isbn9781032316819
oapen.imprintRoutledge
oapen.pages186
oapen.grant.number[...]
peerreview.review.typeProposal
peerreview.anonymitySingle-anonymised
peerreview.reviewer.typeInternal editor
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityPublisher
peerreview.idbc80075c-96cc-4740-a9f3-a234bc2598f1
dc.relationisFundedBye409757c-996d-49d4-9964-b3091fe3d39b
peerreview.titleProposal review


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