Literary Genre Recognition among Polish Blog Posts
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441627" target="_blank" >RIV/00216208:11320/21:10441627 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.procs.2021.08.110" target="_blank" >https://doi.org/10.1016/j.procs.2021.08.110</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2021.08.110" target="_blank" >10.1016/j.procs.2021.08.110</a>
Alternative languages
Result language
angličtina
Original language name
Literary Genre Recognition among Polish Blog Posts
Original language description
Robust methods have been proposed for content and topic-based text classification, as well authorship attribution in stylometry. However, the problem of a fine-grained literary genre (style) recognition is much less studied. We present several approaches to the recognition of eight literary genres manually annotated in a large corpus of Polish blogs. Different text representations were combined with neural network classifiers, including deep, recursive neural networks. Very good results were achieved for the representation of blog posts with the help of pre-trained fastText word embeddings and the Bi-GRU recursive deep neural network as a classifier. As the observed good performance of this classifier could be a result of topical bias across genres, experiments on a selected sub-corpus with a reduced dominance of the most frequent topic were also conducted with no significant change observed. (C) 2021 The Authors. Published by Elsevier B.V.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
—
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Procedia Computer Sciences [online]
ISBN
—
ISSN
1877-0509
e-ISSN
—
Number of pages
10
Pages from-to
1071-1080
Publisher name
ELSEVIER SCIENCE BV
Place of publication
AMSTERDAM
Event location
Szczecin
Event date
Sep 8, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000720289001012