RecSys'11 Workshop on Human Decision Making in Recommender Systems

Alexander Felfernig*, Li CHEN, Monika Mandl

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Interacting with a recommender system means to take different decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera's size, zoom) as criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these scenarios, users have to solve a decision task. The major focuses of this workshop (Decisions@RecSys) were approaches for efficient human decision making in different types of recommendation scenarios.

Original languageEnglish
Title of host publicationRecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems
Pages389
Number of pages1
DOIs
Publication statusPublished - 2011
Event5th ACM Conference on Recommender Systems, RecSys 2011 - Chicago, IL, United States
Duration: 23 Oct 201127 Oct 2011

Publication series

NameRecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems

Conference

Conference5th ACM Conference on Recommender Systems, RecSys 2011
Country/TerritoryUnited States
CityChicago, IL
Period23/10/1127/10/11

Scopus Subject Areas

  • Computer Graphics and Computer-Aided Design
  • Information Systems

User-Defined Keywords

  • decision biases
  • decision making
  • decision psychology
  • recommender algorithms
  • recommender systems

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