Tagsplanations: explaining recommendations using tags

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Tagsplanations: explaining recommendations using tags
While recommender systems tell users what items they might like, explanations of recommendations reveal why they might like them. Explanations provide many benefits, from improving user satisfaction to helping users make better decisions. This paper introduces tagsplanations, which are explanations based on community tags. Tagsplanations have two key components: tag relevance, the degree to which a tag describes an item, and tag preference, the user’s sentiment toward a tag. We develop novel algorithms for estimating tag relevance and tag preference, and we conduct a user study exploring the roles of tag relevance and tag preference in promoting effective tagsplanations. We also examine which types of tags are most useful for tagsplanations. ACM Classification Keywords H.5.3 Information Interfaces and Presentation: Group and Organization Interfaces—Collaborative computing; H.5.2 Information Interfaces and Presentation: User Interfaces General Terms Design, Experimentation, Human...
Jesse Vig, Shilad Sen, John Riedl
Added 17 Mar 2010
Updated 17 Mar 2010
Type Conference
Year 2009
Where IUI
Authors Jesse Vig, Shilad Sen, John Riedl
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