Introduction: This post highlights digital methods and standards for an efficient analysis of historical data.
Category: Data Recognition
Data Recognition, for example OCR, refers to the process of treating the immediate products of digital data capture (recording or imaging), such as digital facsimiles of texts or of sheet music, in a way to extract discrete, machine-readable units from them, such as plain text words, musical notes, or still or moving image elements (including, for example, face recognition).
Introduction: This article discusses the question of minimal sample size in stylometry setting it up as low as 2,000 words in some cases.
Introduction: NeMO is a conceptual framework for DH. It offers a well-founded conceptualization of scholarly work, which can function as schema for a knowledge base containing information on scholarly research activity, including goals, actors, methods, tools and resources involved.
Introduction: This open access article presents the development and the use of a digital tool for linguistic studies.
Introduction: This post outlines some methods and tools for better visualizations and contextual analysis in Ancient History.
Introduction: Here is the presentation of a project in digital archeology with its methods and research process.
Introduction: This French post analyses the data recognition between art and computer.
Introduction: This post presents a number code for authorship identification.
Introduction: This post analyses the sequence alignment text/image and the quality of manuscript transcriptions.
Introduction: This post presents stereotypes on research methods in egyptology, and the current and new projects and tools in this research field.