Computational thematics: comparing algorithms for clustering the genres of literary fiction

What are the best methods of capturing thematic similarity between literary texts? Knowing the answer to this question would be useful for automatic clustering of book genres, or any other thematic grouping. This paper compares a variety of algorithms for unsupervised learning of thematic similariti...

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Bibliographic Details

Published in:	Humanities & social sciences communications Vol. 11; no. 1; pp. 438 - 12
Main Authors:	Sobchuk, Oleg, Šeļa, Artjoms
Format:	Journal Article
Language:	English
Published:	London Springer Nature B.V 01.12.2024 Springer Nature
Subjects:	Algorithms Clustering Crime fiction Extraction Fiction Genre Machine learning Novels Science fiction & fantasy Truth Young adults
ISSN:	2662-9992, 2662-9992
Online Access:	Get full text
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