ComplexRec 2017: Recommendation in Complex Scenarios

Toine Bogers (Redaktør), Marijn Koolen (Redaktør), Bamshad Mobasher (Redaktør), Alan Said (Redaktør), Alexander Tuzhilin (Redaktør)

Publikation: Bog / Antologi / Rapport / Ph.D.-afhandlingAntologiForskningpeer review

Abstract

Recommendation algorithms for ratings prediction and item ranking have steadily matured during the past decade. However, these state-of-the-art algorithms are typically applied in relatively straightforward scenarios. In reality, recommendation is often a more complex problem: it is usually just a single step in the user's more complex background need. These background needs can often place a variety of constraints on which recommendations are interesting to the user and when they are appropriate. However, relatively little research has been done on these complex recommendation scenarios. The ComplexRec 2017 workshop addressed this by providing an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fits-all-solution.
OriginalsprogEngelsk
ForlagCEUR Workshop Proceedings
Antal sider28
StatusUdgivet - 27 aug. 2017
Udgivet eksterntJa
BegivenhedRecSys 2017: 11th ACM Conference on Recommender Systems - Como, Italy, Como, Italien
Varighed: 27 aug. 201731 aug. 2017
Konferencens nummer: 11
https://recsys.acm.org/recsys17/
NavnCEUR Workshop Proceedings
Vol/bind1892
ISSN1613-0073

Konference

KonferenceRecSys 2017: 11th ACM Conference on Recommender Systems
Nummer11
LokationComo, Italy
Land/OmrådeItalien
ByComo
Periode27/08/201731/08/2017
Internetadresse

Emneord

  • Recommendation Algorithms
  • Complex Scenarios
  • User Needs
  • Constraints in Recommendations
  • ComplexRec 2017

Fingeraftryk

Dyk ned i forskningsemnerne om 'ComplexRec 2017: Recommendation in Complex Scenarios'. Sammen danner de et unikt fingeraftryk.

Citationsformater