1. ZHAW digitalcollection
  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-21530
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAghaebrahimian, Ahmad-
dc.contributor.authorCieliebak, Mark-
dc.date.accessioned2021-02-04T10:10:08Z-
dc.date.available2021-02-04T10:10:08Z-
dc.date.issued2020-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21530-
dc.description.abstractNamed Entity Disambiguation (NED) is a crucial task in many Natural Language Processing applications such as entity linking, record linkage, knowledge base construction, or relation extraction, to name a few. The task in NED is to map textual variations of a named entity to its formal name. It has been shown that parameterless models for NED do not generalize to other domains very well. On the other hand, parametric learning models do not scale well when the number of formal names expands above the order of thousands or more. To tackle this problem, we propose a deep architecture with superior performance on NED and introduce a strategy to scale it to hundreds of thousands of formal names. Our experiments on several datasets for alias detection demonstrate that our system is capable of obtaining superior results with a large margin compared to other state-of-the-art systems.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesLecture Notes in Computer Sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectMachine learningde_CH
dc.subjectNamed entity disambiguationde_CH
dc.subjectAlias detectionde_CH
dc.subjectDeep learningde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleNamed entity disambiguation at scalede_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-030-58309-5_8de_CH
dc.identifier.doi10.21256/zhaw-21530-
zhaw.conference.details9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end110de_CH
zhaw.pages.start102de_CH
zhaw.parentwork.editorSchilling, Frank-Peter-
zhaw.parentwork.editorStadelmann, Thilo-
zhaw.publication.statusacceptedVersionde_CH
zhaw.series.number12294de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsArtificial Neural Networks in Pattern Recognitionde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedNatural Language Processingde_CH
zhaw.funding.zhawAuSuM - Automatic Supply Chain Monitoringde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

Files in This Item:
File Description SizeFormat 
2020_Aghaebrahimian-Cieliebak_Named-entity-disambiguation-at-scale.pdfAccepted Version141.79 kBAdobe PDFThumbnail
View/Open
Show simple item record
Aghaebrahimian, A., & Cieliebak, M. (2020). Named entity disambiguation at scale [Conference paper]. In F.-P. Schilling & T. Stadelmann (Eds.), Artificial Neural Networks in Pattern Recognition (pp. 102–110). Springer. https://doi.org/10.1007/978-3-030-58309-5_8
Aghaebrahimian, A. and Cieliebak, M. (2020) ‘Named entity disambiguation at scale’, in F.-P. Schilling and T. Stadelmann (eds) Artificial Neural Networks in Pattern Recognition. Cham: Springer, pp. 102–110. Available at: https://doi.org/10.1007/978-3-030-58309-5_8.
A. Aghaebrahimian and M. Cieliebak, “Named entity disambiguation at scale,” in Artificial Neural Networks in Pattern Recognition, 2020, pp. 102–110. doi: 10.1007/978-3-030-58309-5_8.
AGHAEBRAHIMIAN, Ahmad und Mark CIELIEBAK, 2020. Named entity disambiguation at scale. In: Frank-Peter SCHILLING und Thilo STADELMANN (Hrsg.), Artificial Neural Networks in Pattern Recognition. Conference paper. Cham: Springer. 2020. S. 102–110
Aghaebrahimian, Ahmad, and Mark Cieliebak. 2020. “Named Entity Disambiguation at Scale.” Conference paper. In Artificial Neural Networks in Pattern Recognition, edited by Frank-Peter Schilling and Thilo Stadelmann, 102–10. Cham: Springer. https://doi.org/10.1007/978-3-030-58309-5_8.
Aghaebrahimian, Ahmad, and Mark Cieliebak. “Named Entity Disambiguation at Scale.” Artificial Neural Networks in Pattern Recognition, edited by Frank-Peter Schilling and Thilo Stadelmann, Springer, 2020, pp. 102–10, https://doi.org/10.1007/978-3-030-58309-5_8.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.