Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Document Clustering Using Attentive Hierarchical Document Representation
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundation of Language Processing)ORCID iD: 0000-0002-6791-8284
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)ORCID iD: 0000-0001-7349-7693
2020 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

We propose a text clustering algorithm that applies an attention mechanism on both word andsentence level. This ongoing work is motivated by an application in contextual programmatic advertising, where the goal is to grouponline articles into clusters corresponding to agiven set of marketing objectives. The maincontribution is the use of attention to identify words and sentences that are of specific importance for the formation of the clusters

Place, publisher, year, edition, pages
2020.
Keywords [en]
Document Clustering, Document Representation, Attention Mechanism
National Category
Language Technology (Computational Linguistics) Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-180628OAI: oai:DiVA.org:umu-180628DiVA, id: diva2:1530123
Conference
SLTC 2020 – The Eighth Swedish Language Technology Conference, Online, November 25–27, 2020
Available from: 2021-02-21 Created: 2021-02-21 Last updated: 2021-09-06Bibliographically approved

Open Access in DiVA

fulltext(667 kB)99 downloads
File information
File name FULLTEXT01.pdfFile size 667 kBChecksum SHA-512
399965c702db869c50b3e3a0d531436b1ea0578c8e4a98eb61dcde0ea35b170a12834c2861827fd8728207c3725c0e5d9016ffde604d208029d66f25a08e495f
Type fulltextMimetype application/pdf

Other links

URL

Authority records

Hatefi, ArezooDrewes, Frank

Search in DiVA

By author/editor
Hatefi, ArezooDrewes, Frank
By organisation
Department of Computing Science
Language Technology (Computational Linguistics)Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 99 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 330 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf