v-trel: Vocabulary Trainer for Tracing Word Relations : An Implicit Crowdsourcing Approach

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dc.contributor.author Lyding, Verena
dc.contributor.author Rodosthenous, Christos
dc.contributor.author Sangati, Federico
dc.contributor.author Ul Hassan, Umair
dc.contributor.author Nicolas, Lionel
dc.contributor.author König, Alexander
dc.contributor.author Horbacauskiene, Jolita
dc.contributor.author Katinskaia, Anisia
dc.contributor.editor Angelova, Galia
dc.contributor.editor Mitkov, Ruslan
dc.contributor.editor Nikolova, Ivelina
dc.contributor.editor Temnikova, Irina
dc.date.accessioned 2020-01-20T09:37:01Z
dc.date.available 2020-01-20T09:37:01Z
dc.date.issued 2019-09
dc.identifier.citation Lyding , V , Rodosthenous , C , Sangati , F , Ul Hassan , U , Nicolas , L , König , A , Horbacauskiene , J & Katinskaia , A 2019 , v-trel: Vocabulary Trainer for Tracing Word Relations : An Implicit Crowdsourcing Approach . in G Angelova , R Mitkov , I Nikolova & I Temnikova (eds) , RANLP 2019 - Natural Language Processing a Deep Learning World : Proceedings . INCOMA , Shoumen , pp. 675-684 , Recent Advances in Natural Language Processing , Varna , Bulgaria , 02/09/2019 . https://doi.org/10.26615/978-954-452-056-4_079
dc.identifier.citation conference
dc.identifier.other PURE: 130218663
dc.identifier.other PURE UUID: 1a591780-2bbd-4d35-9a08-af10f55f9282
dc.identifier.uri http://hdl.handle.net/10138/309834
dc.description.abstract In this paper, we present our work on developing a vocabulary trainer that uses exercises generated from language resources such as ConceptNet and crowdsources the responses of the learners to enrich the language resource. We performed an empirical evaluation of our approach with 60 non-native speakers over two days, which shows that new entries to expand Concept-Net can efficiently be gathered through vocabulary exercises on word relations. We also report on the feedback gathered from the users and an expert from language teaching, and discuss the potential of the vocabulary trainer application from the user and language learner perspective. The feedback suggests that v-trel has educational potential, while in its current state some shortcomings could be identified. en
dc.format.extent 10
dc.language.iso eng
dc.publisher INCOMA
dc.relation.ispartof RANLP 2019 - Natural Language Processing a Deep Learning World
dc.relation.isversionof 978-954-452-055-7
dc.relation.isversionof 978-954-452-056-4
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 113 Computer and information sciences
dc.title v-trel: Vocabulary Trainer for Tracing Word Relations : An Implicit Crowdsourcing Approach en
dc.type Conference contribution
dc.contributor.organization Department of Digital Humanities
dc.contributor.organization Department of Computer Science
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.26615/978-954-452-056-4_079
dc.rights.accesslevel openAccess
dc.type.version publishedVersion
dc.identifier.url http://lml.bas.bg/ranlp2019/proceedings-ranlp-2019.pdf

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