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.
|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|