Quantitative Intertextuality Analyzing the Markers of Information Reuse /

• Main Authors: Forstall, Christopher W. (Author, http://id.loc.gov/vocabulary/relators/aut), Scheirer, Walter J. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Subjects: Artificial intelligence.; Information storage and retrieval.; Pattern recognition.; Application software.; Cultural studies.; Artificial Intelligence.; Information Storage and Retrieval.; Pattern Recognition.; Computer Appl. in Social and Behavioral Sciences.; Cultural Studies.

This book introduces quantitative intertextuality, a new approach to the algorithmic study of information reuse in text, sound and images. Employing a variety of tools from machine learning, natural language processing, and computer vision, readers will learn to trace patterns of reuse across divers...

Table of Contents:

• What is Quantitative Intertextuality
• Statistical Learning as a Model for Intertextuality
• Lexical Matching: Text Reuse as Intertextuality
• Semantic Matching: Tracing Reuse by Meaning
• Sound Matching: Capturing Reuse in the Primitive Elements of Language
• Image Matching: Detecting the Reuse of Visual Elements
• Meta-Matching: Combining Evidence From Heterogeneous Sources
• Parting Thoughts.