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dc.identifier.uri Asheghi, Noushin Rezapour Sharoff, Serge Markert, Katja 2017-01-12T08:35:30Z 2017-01-12T08:35:30Z 2016
dc.identifier.citation Asheghi, N.R.; Sharoff, S.; Markert, K.: Crowdsourcing for web genre annotation. In: Language Resources and Evaluation 50 (2016), Nr. 3, S. 603-641. DOI:
dc.description.abstract Recently, genre collection and automatic genre identification for the web has attracted much attention. However, currently there is no genre-annotated corpus of web pages where inter-annotator reliability has been established, i.e. the corpora are either not tested for inter-annotator reliability or exhibit low inter-coder agreement. Annotation has also mostly been carried out by a small number of experts, leading to concerns with regard to scalability of these annotation efforts and transferability of the schemes to annotators outside these small expert groups. In this paper, we tackle these problems by using crowd-sourcing for genre annotation, leading to the Leeds Web Genre Corpus—the first web corpus which is, demonstrably reliably annotated for genre and which can be easily and cost-effectively expanded using naive annotators. We also show that the corpus is source and topic diverse. © 2016, The Author(s). eng
dc.description.sponsorship Google Research Award
dc.description.sponsorship EPSRC Doctoral Training Grant
dc.language.iso eng
dc.publisher Dordrecht : Springer Netherlands
dc.relation.ispartofseries Language Resources and Evaluation 50 (2016), Nr. 3
dc.rights CC BY 4.0 Unported
dc.subject Annotation guidelines eng
dc.subject Crowdsourcing eng
dc.subject Genres on the web eng
dc.subject Reliability testing eng
dc.subject.ddc 004 | Informatik ger
dc.title Crowdsourcing for web genre annotation
dc.type article
dc.type Text
dc.relation.issn 1574-020X
dc.bibliographicCitation.issue 3
dc.bibliographicCitation.volume 50
dc.bibliographicCitation.firstPage 603
dc.bibliographicCitation.lastPage 641
dc.description.version publishedVersion
tib.accessRights frei zug�nglich

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