xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance

Y Shi, A Karatzoglou, L Baltrunas, MA Larson, A Hanjalic

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

37 Citations (Scopus)
Original languageEnglish
Title of host publicationProceedings of the 7th ACM conference on Recommender systems (RecSys '13)
Editors SN
Place of PublicationNY, NY, USA
PublisherAssociation for Computing Machinery (ACM)
Pages431-434
Number of pages4
ISBN (Print)978-1-4503-2409-0
Publication statusPublished - 2013
Event7th ACM conference on Recommender systems, RecSys 2013 -
Duration: 12 Oct 201316 Oct 2013

Publication series

Name
PublisherACM

Conference

Conference7th ACM conference on Recommender systems, RecSys 2013
Period12/10/1316/10/13

Keywords

  • conference contrib. refereed
  • Conf.proc. > 3 pag

Cite this

Shi, Y., Karatzoglou, A., Baltrunas, L., Larson, MA., & Hanjalic, A. (2013). xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance. In SN (Ed.), Proceedings of the 7th ACM conference on Recommender systems (RecSys '13) (pp. 431-434). Association for Computing Machinery (ACM).