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Text and Image Mining for Historical Research

Scholars in history and other humanities tend to work differently than their colleagues in science and engineering. Working alone or occasionally in small groups, their focus is typically on the close reading of sources, including text and images. Mathematica's high-level commands and holistic approach make it possible for a single programmer to implement relatively complex research tools that are customized for a particular study. Here William Turkel describes a few examples, including the mining and conceptual analysis of text, and image mining applied to electronic schematics, photographs of bridges and the visual culture of stage magic. He also discuss the opportunities and challenges of teaching these kinds of skills to university students with little or no technical background.

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Channels: Wolfram Virtual Technology Conference 2020

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