Collaborative information finding in smaller communities: The case of research talks

International Journal of Human-Computer Studies

2015

Self Cite

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.

Section: Recommendation Approachesmentioning

confidence: 99%

User-controllable personalization: A case study with SetFusion

Parra

International Journal of Human-Computer Studies

2015

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“…The second version of Conference Navigator, CNII (Brusilovsky, Parra, Sahebi, & Wongchokprasitti, 2010;, enhanced the original set of social navigation techniques with the use of tags (which are among the most useful types of community wisdom) and added the ability to track users' actions, not only at the group level, but also at the individual level. In turn, these data allowed developing and evaluating some more advanced social navigation approaches.…”

Section: Which Presentation Should I Attend?mentioning

confidence: 99%

Linking information and people in a social system for academic conferences

New Review of Hypermedia and Multimedia

López

et al. 2016

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This paper investigates the feasibility of maintaining a social information system to support attendees at an academic conference. The main challenge of this work was to create an infrastructure where users' social activities, such as bookmarking, tagging, and social linking could be used to enhance user navigation and maximize the users' ability to locate two important types of information in conference settings: presentations to attend and attendees to meet. We developed Conference Navigator 3, a social conference support system that integrates a conference schedule planner with a social linking service. We examined its potential and functions in the context of a mediumscale academic conference. In this paper, we present the design of the system's socially enabled features and report the results of a conference-based study. Our study demonstrates the feasibility of social information systems for supporting academic conferences. Despite the low number of potential users and the short timeframe in which conferences took place, the usage of the system was high enough to provide sufficient data for social mechanisms. The study shows that most critical social features were highly appreciated and used, and provides direction for further research. ARTICLE HISTORY

“…CN3 leverages several sources of knowledge to generate recommendations including talk content (title and abstract), user tags, and user social connections [4]. Given their particular strengths and weaknesses, we believed that users should be aware of which sources were used to recommend a specific talk and have some level of control over the source selection in a recommender.…”

Section: The Recommender Interfacementioning

confidence: 99%

See what you want to see

Parra

Proceedings of the 19th International Conference on Intelligent User Interfaces

Trattner

2014

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Research in recommender systems has traditionally focused on improving the predictive accuracy of recommendations by developing new algorithms or by incorporating new sources of data. However, several studies have shown that accuracy does not always correlate with a better user experience, leading to recent research that puts emphasis on HumanComputer Interaction in order to investigate aspects of the interface and user characteristics that influence the user experience on recommender systems. Following this new research this paper presents SetFusion, a visual user-controllable interface for hybrid recommender system. Our approach enables users to manually fuse and control the importance of recommender strategies and to inspect the fusion results using an interactive Venn diagram visualization. We analyze the results of two field studies in the context of a conference talk recommendation system, performed to investigate the effect of user controllability in a hybrid recommender. Behavioral analysis and subjective evaluation indicate that the proposed controllable interface had a positive effect on the user experience.