In this paper we present the first results of stylometric analysis of literary papyri. Specifically we perform a range of tests for unsupervised clustering of authors. We scrutinise both the best classic distance-based methods as well as the state-of-the-art network community detection techniqes. We report on obstacles concerning highly non-uniform distributions of text size and authorial samples combined with sparse feature space. We also note how clustering performance depends on regularisation of spelling by means of querying relevant annotations.
Autori: | |
Data di pubblicazione: | 2019 |
Titolo: | Stylometry of literary papyri |
Titolo del libro: | ACM International Conference Proceeding Series |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1145/3322905.3322930 |
Appare nelle tipologie: | 4.1 Articolo in Atti di convegno |
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