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Author Profiling and Plagiarism Detection

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Author Profiling and Plagiarism Detection

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dc.contributor.author Rosso, Paolo es_ES
dc.date.accessioned 2016-09-15T09:46:17Z
dc.date.available 2016-09-15T09:46:17Z
dc.date.issued 2015
dc.identifier.isbn 978-3-319-25484-5
dc.identifier.issn 1865-0929
dc.identifier.uri http://hdl.handle.net/10251/69618
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-25485-2_6 es_ES
dc.description.abstract In this chapter we introduce the topics that we will cover in the RuSSIR 2014 course on Author Profiling and Plagiarism Detection (APPD). Author profiling distinguishes between classes of authors studying how language is shared by classes of people. This task helps in identifying profiling aspects such as gender, age, native language, or even personality type. In case of the plagiarism detection task we are not interested in studying how language is shared. On the contrary, given a document we are interested in investigating if the writing style changes in order to unveil text inconsistencies, i.e., unexpected irregularities through the document such as changes in vocabulary, style and text complexity. In fact, when it is not possible to retrieve the source document(s) where plagiarism has been committed from, the intrinsic analysis of the suspicious document is the only way to find evidence of plagiarism. The difficulty in retrieving the source of plagiarism could be due to the fact that the documents are not available on the web or the plagiarised text fragments were obfuscated via paraphrasing or translation (in case the source document was in another language). In this overview, we also discuss the results of the shared tasks on author profiling (gender and age identification) and plagiarism detection that we help to organise at the PAN Lab on Uncovering Plagiarism, Authorship, and Social Software Misuse. es_ES
dc.description.sponsorship The PAN shared tasks on author profil-ing and on plagiarism detection have been organised in the framework of the WIQ-EIIRSES project (Grant No. 269180) within the EC FP 7 Marie Curie People. The research work described in the paper was carried out in the framework of the DIANA-APPLICATIONS-Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project, and the VLC/CAMPUS Microcluster on Multimodal Interaction inIntelligent Systems. es_ES
dc.format.extent 22 es_ES
dc.language Inglés es_ES
dc.publisher Springer es_ES
dc.relation.ispartof Information Retrieval es_ES
dc.relation.ispartofseries Communications in Computer and Information Science;505
dc.rights Reserva de todos los derechos es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Author Profiling and Plagiarism Detection es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1007/978-3-319-25485-2_6
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/269180/EU/Web Information Quality Evaluation Initiative/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2012-38603-C02-01/ES/DIANA-APPLICATIONS: FINDING HIDDEN KNOWLEDGE IN TEXTS: APPLICATIONS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Rosso, P. (2015). Author Profiling and Plagiarism Detection. En Information Retrieval. Springer. 229-250. https://doi.org/10.1007/978-3-319-25485-2_6 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 8th Russian Summer School in Information Retrieval (RuSSIR 2014) es_ES
dc.relation.conferencedate August 18-22, 2014 es_ES
dc.relation.conferenceplace Nizhny Novgorod, Russia es_ES
dc.relation.publisherversion http://link.springer.com/chapter/10.1007/978-3-319-25485-2_6 es_ES
dc.description.upvformatpinicio 229 es_ES
dc.description.upvformatpfin 250 es_ES
dc.relation.senia 306169 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Universitat de València es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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