ОписПодробиці та характеристикиПрикріплені файли
AI-Powered Digitization of Historical Records: Architectures, Pipelines, and Scaling Strategies provides a comprehensive study of modern approaches to the digital transformation of historical and archival data using artificial intelligence.
The book examines the architectural principles, technological strategies, and engineering solutions required to build scalable systems for processing historical information. The author details the application of OCR, machine learning, Natural Language Processing (NLP), Large Language Models (LLMs), cloud technologies, and distributed computing to transform unstructured archival materials into structured digital knowledge.
Special attention is dedicated to scaling AI infrastructure, automating document processing, data management, building high-performance information pipelines, and creating advanced digital archival ecosystems. The book bridges theoretical foundations with practical experience derived from global-scale projects involving the digitization of censuses, historical newspapers, city directories, and other archival collections.
This publication will be a valuable resource for software engineers, AI architects, data professionals, digital humanities researchers, archivists, librarians, digital transformation project managers, and anyone working at the intersection of artificial intelligence, big data, and cultural heritage preservation.This book demonstrates how modern AI technologies can not only preserve history but also transform it into an accessible, structured, and invaluable source of knowledge for future generations.
ISBN 978-617-8660-48-2https://doi.org/10.66481/978-617-8660-48-2
The book examines the architectural principles, technological strategies, and engineering solutions required to build scalable systems for processing historical information. The author details the application of OCR, machine learning, Natural Language Processing (NLP), Large Language Models (LLMs), cloud technologies, and distributed computing to transform unstructured archival materials into structured digital knowledge.
Special attention is dedicated to scaling AI infrastructure, automating document processing, data management, building high-performance information pipelines, and creating advanced digital archival ecosystems. The book bridges theoretical foundations with practical experience derived from global-scale projects involving the digitization of censuses, historical newspapers, city directories, and other archival collections.
This publication will be a valuable resource for software engineers, AI architects, data professionals, digital humanities researchers, archivists, librarians, digital transformation project managers, and anyone working at the intersection of artificial intelligence, big data, and cultural heritage preservation.This book demonstrates how modern AI technologies can not only preserve history but also transform it into an accessible, structured, and invaluable source of knowledge for future generations.
ISBN 978-617-8660-48-2https://doi.org/10.66481/978-617-8660-48-2