Computational thematics: comparing algorithms for clustering the genres of literary fiction
Abstract 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 s...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2024-03-01
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| Series: | Humanities & Social Sciences Communications |
| Online Access: | https://doi.org/10.1057/s41599-024-02933-6 |
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