Interaction design guidelines representatives. According to their respective characteristics, we summarize two main elements that can be varied to reflect different degrees of user control. We then intro- duce a user evaluation framework with major dependent variables measured in our experiments. Detailed descriptions of three user-trials then follow, including their materials, recruited participants, experimental procedures, results analyses and dis- cussions. Finally, we conclude our work and indicate its practical implications and future directions 2 Critiquingbased recommender systems Our investigation of existing critiquing-based recommender systems revealed that they basically follow a similar interaction model(see Fig. 1). The user first specifies her initial preferences on product attributes. The system then returns one or multiple rec- ommended items. either the user selects an item as her final choice and terminates the interaction, or she makes critiques by picking system-suggested critiques or defining critiques herself. If critiques were made, the system updates the recommendation(s) and the list of suggested critiques (if provided) in the next interaction cycle. This process continues until the user decides that she has found her most preferred product Most of existing systems fall into two specific branches: one is called single-item system-suggested critiquing since it recommends one item at a time and guides users to provide feedback by selecting a system-suggested critique; another d k-item tion cycle and: quing, because it provides multiple items during each recommenda- and creating their self-specified critiquing criteria to the product. In the following, we will introduce both approaches in detail with two typical applications as examples 2. 1 Single-item system-suggested critiquing The FindMe system was the first known single-item system-suggested critiquing sys- tem(Burke et al. 1996, 1997). It uses knowledge about the product domain to help user One or multiple example outcomes are 1 displayed Iggested and/or are elicited critiquing Fig. 1 The typical interaction model of a critiquing-based recommender systemInteraction design guidelines 171 representatives. According to their respective characteristics, we summarize two main elements that can be varied to reflect different degrees of user control. We then intro￾duce a user evaluation framework with major dependent variables measured in our experiments. Detailed descriptions of three user-trials then follow, including their materials, recruited participants, experimental procedures, results analyses and dis￾cussions. Finally, we conclude our work and indicate its practical implications and future directions. 2 Critiquing-based recommender systems Our investigation of existing critiquing-based recommender systems revealed that they basically follow a similar interaction model (see Fig. 1). The user first specifies her initial preferences on product attributes. The system then returns one or multiple rec￾ommended items. Either the user selects an item as her final choice and terminates the interaction, or she makes critiques by picking system-suggested critiques or defining critiques herself. If critiques were made, the system updates the recommendation(s) and the list of suggested critiques (if provided) in the next interaction cycle. This process continues until the user decides that she has found her most preferred product. Most of existing systems fall into two specific branches: one is called single-item system-suggested critiquing since it recommends one item at a time and guides users to provide feedback by selecting a system-suggested critique; another is called k-item user-initiated critiquing, because it provides multiple items during each recommenda￾tion cycle and a critiquing aid that assists users in choosing one product to be critiqued and creating their self-specified critiquing criteria to the product. In the following, we will introduce both approaches in detail with two typical applications as examples. 2.1 Single-item system-suggested critiquing The FindMe system was the first known single-item system-suggested critiquing sys￾tem (Burke et al. 1996, 1997). It uses knowledge about the product domain to help users accept User s initial preferences are elicited One or multiple example outcomes are displayed No more effort required System￾suggested and/or user-initiated critiquing Fig. 1 The typical interaction model of a critiquing-based recommender system 123