Automatic Adaptation of Author's Stylometric Features to Document Types
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00073237" target="_blank" >RIV/00216224:14330/14:00073237 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-10816-2_7" target="_blank" >http://dx.doi.org/10.1007/978-3-319-10816-2_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-10816-2_7" target="_blank" >10.1007/978-3-319-10816-2_7</a>
Alternative languages
Result language
angličtina
Original language name
Automatic Adaptation of Author's Stylometric Features to Document Types
Original language 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).
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/VF20102014003" target="_blank" >VF20102014003: Natural Language Analysis in the Internet Environment</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Text, Speech, and Dialogue - 17th International Conference
ISBN
9783319108155
ISSN
0302-9743
e-ISSN
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Number of pages
9
Pages from-to
53-61
Publisher name
Springer International Publishing
Place of publication
Switzerland
Event location
Brno
Event date
Sep 8, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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