About: Automatic Adaptation of Author's Stylometric Features to Document Types

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Many Internet users face the problem of anonymous documents and texts with a counterfeit authorship. The number of questionable documents exceeds the capacity of human experts, therefore a universal automated authorship identification system supporting all types of documents is needed. In this paper, five predominant document types are analysed in the context of the authorship verification: books, blogs, discussions, comments and tweets. A method of an automatic selection of authors’ stylometric features using a double-layer machine learning is proposed and evaluated. Experiments are conducted on ten disjunct train and test sets and a method of an efficient training of large number of machine learning models is introduced (163,700 models were trained). Many Internet users face the problem of anonymous documents and texts with a counterfeit authorship. The number of questionable documents exceeds the capacity of human experts, therefore a universal automated authorship identification system supporting all types of documents is needed. In this paper, five predominant document types are analysed in the context of the authorship verification: books, blogs, discussions, comments and tweets. A method of an automatic selection of authors’ stylometric features using a double-layer machine learning is proposed and evaluated. Experiments are conducted on ten disjunct train and test sets and a method of an efficient training of large number of machine learning models is introduced (163,700 models were trained). (en)
Title	Automatic Adaptation of Author's Stylometric Features to Document Types Automatic Adaptation of Author's Stylometric Features to Document Types (en)
skos:prefLabel	Automatic Adaptation of Author's Stylometric Features to Document Types Automatic Adaptation of Author's Stylometric Features to Document Types (en)
skos:notation	RIV/00216224:14330/14:00073237!RIV15-MV0-14330___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(VF20102014003), S
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Rygl, Jan
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Fakulta informatiky
http://linked.open...dnocenehoVysledku	4572
http://linked.open...ai/riv/idVysledku	RIV/00216224:14330/14:00073237
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	authorship verification; feature selection; machine learning; stylome; stylometric features (en)
http://linked.open.../riv/klicoveSlovo	feature selection authorship verification machine learning stylome stylometric features
http://linked.open...ontrolniKodProRIV	[A5C361B3B461]
http://linked.open...v/mistoKonaniAkce	Brno
http://linked.open...i/riv/mistoVydani	Switzerland
http://linked.open...i/riv/nazevZdroje	Text, Speech, and Dialogue - 17th International Conference
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Natural Language Analysis in the Internet Environment
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Rygl, Jan
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-09-08 (xsd:date)
issn	0302-9743
number of pages	9 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-319-10816-2_7
http://purl.org/ne...btex#hasPublisher	Springer International Publishing
https://schema.org/isbn	9783319108155
http://localhost/t...ganizacniJednotka	14330

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