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rdf:type
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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)
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Title
| - Automatic Adaptation of Author's Stylometric Features to Document Types
- Automatic Adaptation of Author's Stylometric Features to Document Types (en)
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skos:prefLabel
| - Automatic Adaptation of Author's Stylometric Features to Document Types
- Automatic Adaptation of Author's Stylometric Features to Document Types (en)
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skos:notation
| - RIV/00216224:14330/14:00073237!RIV15-MV0-14330___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216224:14330/14:00073237
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - authorship verification; feature selection; machine learning; stylome; stylometric features (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - Text, Speech, and Dialogue - 17th International Conference
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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issn
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number of pages
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http://bibframe.org/vocab/doi
| - 10.1007/978-3-319-10816-2_7
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http://purl.org/ne...btex#hasPublisher
| - Springer International Publishing
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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