To increase the user experience, preference elicitation methods used by recommender systems can be adapted to individual differences such as the level of expertise. However, we will show that the satisfaction and perceived usefulness of a recommender system also depends strongly on subtle variations of the implementation of these methods
Two problemsmay arisewhen an intelligent (recommender) system elicits users’ preferences. First, the...
232 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.A total of 401 subjects parti...
We address user system interaction issues in product search and recommender systems: how to help use...
To increase the user experience, preference elicitation methods used by recommender systems can be a...
In a recommender system that suggests options based on user attribute weights, the method of prefere...
Recommender systems persuade as well as recommend. This study investigated some factors that influen...
Research on recommender systems typically focuses on the accuracy of prediction algorithms. Because ...
This paper compares five different ways of interacting with an attribute-based recommender system an...
This paper systematically evaluates the user experience of a recommender system. Using both behavior...
Two problemsmay arisewhen an intelligent (recommender) system elicits users’ preferences. First, the...
232 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.A total of 401 subjects parti...
We address user system interaction issues in product search and recommender systems: how to help use...
To increase the user experience, preference elicitation methods used by recommender systems can be a...
In a recommender system that suggests options based on user attribute weights, the method of prefere...
Recommender systems persuade as well as recommend. This study investigated some factors that influen...
Research on recommender systems typically focuses on the accuracy of prediction algorithms. Because ...
This paper compares five different ways of interacting with an attribute-based recommender system an...
This paper systematically evaluates the user experience of a recommender system. Using both behavior...
Two problemsmay arisewhen an intelligent (recommender) system elicits users’ preferences. First, the...
232 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.A total of 401 subjects parti...
We address user system interaction issues in product search and recommender systems: how to help use...