kth.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
Third Workshop on Recommender Systems in Fashion-fashionXrecsys2021
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-7786-9551
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0003-2339-2337
Spotify, Amsterdam, Sweden..
Zalando SE, Berlin, Germany..
2021 (English)In: 15Th Acm Conference On Recommender Systems (Recsys 2021), Association for Computing Machinery (ACM) , 2021, p. 810-812Conference paper, Published paper (Refereed)
Abstract [en]

Online Fashion retailers have significantly increased in popularity over the last decade, making it possible for customers to explore hundreds of thousands of products without the need to visit multiple stores or stand in long queues for checkout. Recommender Systems are often used to solve different complex problems in this domain, such as social fashion-aware recommendations (outfits inspired by influencers), product recommendations, or size and fit recommendations. Moreover, the research interest on this area is increasing, demonstrated by the success of the first and second editions of the fashionXrecsys Workshop in 2019-2020. The third edition of the workshop aims at providing an avenue for continuing the discussion of novel approaches and applications of recommendation systems in fashion and e-commerce.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2021. p. 810-812
Keywords [en]
Recommendations, Fashion, E-Commerce, Social Networks, Deep Learning, Computer Vision
National Category
Business Administration
Identifiers
URN: urn:nbn:se:kth:diva-309301DOI: 10.1145/3460231.3470926ISI: 000744461300123Scopus ID: 2-s2.0-85115624218OAI: oai:DiVA.org:kth-309301DiVA, id: diva2:1641295
Conference
15th ACM Conference on Recommender Systems (RECSYS), SEP 27-OCT 01, 2021, Amsterdam, NETHERLANDS
Note

QC 20220301

Part of proceedings ISBN: 978-1-4503-8458-2

Available from: 2022-03-01 Created: 2022-03-01 Last updated: 2022-06-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Jaradat, ShathaDokoohaki, Nima

Search in DiVA

By author/editor
Jaradat, ShathaDokoohaki, Nima
By organisation
Software and Computer systems, SCS
Business Administration

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 93 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