Titlebook: Quantitative Intertextuality; Analyzing the Marker Christopher W. Forstall,Walter J. Scheirer Book 2019 Springer Nature Switzerland AG 2019

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Meta-Matching: Combining Evidence From Heterogeneous SourcesIn many instances, one piece of evidence alone will not be enough to make an accurate decision about the intertextual relationship between two texts. More evidence, combined in a probabilistic way, can improve our confidence in a classification result.

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Parting ThoughtsThe richness of human experience is often derived not from what is new, but from what is familiar. Throughout this book, we have seen numerous examples of this observation play out, from the sublime of the world’s best literature, to the ordinariness of visual scenes.

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https://doi.org/10.1007/978-3-030-23415-7Information Retrieval; Information Reuse; Authorship Attribution; Pattern Matching; Cultural Studies

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ntitative methods for a large number of practical problems, 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,

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What is Quantitative Intertextuality?xture in disciplines in the humanities such as semiotics, comparative literature, classical studies and others concerned with the provenance of information. Julia Kristeva, who coined the term intertext, suggested, “Any text is constructed as a mosaic of quotations; any text is the absorption and tr

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