Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-1528
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dc.contributor.authorvon Däniken, Pius-
dc.contributor.authorCieliebak, Mark-
dc.date.accessioned2017-12-14T14:19:12Z-
dc.date.available2017-12-14T14:19:12Z-
dc.date.issued2017-09-07-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/1854-
dc.description.abstractWe present our system for the WNUT 2017 Named Entity Recognition challenge on Twitter data. We describe two modi- fications of a basic neural network architecture for sequence tagging. First, we show how we exploit additional labeled data, where the Named Entity tags differ from the target task. Then, we propose a way to incorporate sentence level features. Our system uses both methods and ranked second for entity level annotations, achieving an F1-score of 40.78, and second for surface form annotations, achieving an F1- score of 39.33.de_CH
dc.language.isoende_CH
dc.publisherAssociation for Computational Linguisticsde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectNamed Entity Recogintionde_CH
dc.subjectNERde_CH
dc.subject.ddc004: Informatikde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleTransfer learning and sentence level features for named entity recognition on tweetsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Angewandte Informationstechnologie (InIT)de_CH
dc.identifier.doi10.21256/zhaw-1528de_CH
zhaw.conference.details3rd Workshop on Noisy User-generated Text (W-NUT), Copenhagen, September 7th, 2017de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end171de_CH
zhaw.pages.start166de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume3de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsProceedings of the 3rd Workshop on Noisy User-generated Textde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedSoftware Systemsde_CH
Appears in Collections:Publikationen School of Engineering

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