Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing - CSCW Companion '14, 2014
ABSTRACT In this research we investigated the role of user controllability on personalized system... more ABSTRACT In this research we investigated the role of user controllability on personalized systems by implementing and studying a novel interactive recommender interface, SetFusion. We examined whether allowing the user to control the process of fusing or integrating different algorithms (i.e., different sources of relevance) resulted in increased engagement and a better user experience. The essential contribution of this research stems from the results of a user study (N=40) of controllability in a scenario where users could fuse different recommendation approaches, with the possibility of inspecting and filtering the items recommended. First, we introduce an interactive Venn diagram visualization, which combined with sliders, can provide an efficient visual paradigm for information filtering. Second, we provide a three-fold evaluation of the user experience: objective metrics, subjective user perception, and behavioral measures. Through the analysis of these metrics, we confirmed results from recent studies, such as the effect of trusting propensity on accepting the recommendations and also unveiled the importance of features such as being a native speaker. Our results present several implications for the design and implementation of user-controllable personalized systems.
ABSTRACT In this paper, we contribute to the study of recommender systems from a HCI perspective ... more ABSTRACT In this paper, we contribute to the study of recommender systems from a HCI perspective by investigating the effects upon the user experience of a novel interface which uses a Venn diagram to represent the outputs of an interactive talk recommender system. We present the results of a preliminary user study on talk recommendations in the context of a conference with n=37 people that used our system under one of two conditions: a static list of recommendations, or the enhanced visual controllable interface. The user behavioral analysis and the results of a survey that n=17 users answered provide interesting insights for designers and developers of interfaces for recommender systems, especially when the items can have one or more contexts of relevancy as in a hybrid recommender system.
Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing - CSCW Companion '14, 2014
ABSTRACT In this research we investigated the role of user controllability on personalized system... more ABSTRACT In this research we investigated the role of user controllability on personalized systems by implementing and studying a novel interactive recommender interface, SetFusion. We examined whether allowing the user to control the process of fusing or integrating different algorithms (i.e., different sources of relevance) resulted in increased engagement and a better user experience. The essential contribution of this research stems from the results of a user study (N=40) of controllability in a scenario where users could fuse different recommendation approaches, with the possibility of inspecting and filtering the items recommended. First, we introduce an interactive Venn diagram visualization, which combined with sliders, can provide an efficient visual paradigm for information filtering. Second, we provide a three-fold evaluation of the user experience: objective metrics, subjective user perception, and behavioral measures. Through the analysis of these metrics, we confirmed results from recent studies, such as the effect of trusting propensity on accepting the recommendations and also unveiled the importance of features such as being a native speaker. Our results present several implications for the design and implementation of user-controllable personalized systems.
ABSTRACT In this paper, we contribute to the study of recommender systems from a HCI perspective ... more ABSTRACT In this paper, we contribute to the study of recommender systems from a HCI perspective by investigating the effects upon the user experience of a novel interface which uses a Venn diagram to represent the outputs of an interactive talk recommender system. We present the results of a preliminary user study on talk recommendations in the context of a conference with n=37 people that used our system under one of two conditions: a static list of recommendations, or the enhanced visual controllable interface. The user behavioral analysis and the results of a survey that n=17 users answered provide interesting insights for designers and developers of interfaces for recommender systems, especially when the items can have one or more contexts of relevancy as in a hybrid recommender system.
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