Interaction Tasks for Explainable Recommender Systems

dc.contributor.authorAl-Hazwani, Ibrahimen_US
dc.contributor.authorAlahmadi, Turkien_US
dc.contributor.authorWardatzky, Kathrinen_US
dc.contributor.authorInel, Oanaen_US
dc.contributor.authorEl-Assady, Mennatallahen_US
dc.contributor.authorBernard, Jürgenen_US
dc.contributor.editorGillmann, Christinaen_US
dc.contributor.editorKrone, Michaelen_US
dc.contributor.editorLenti, Simoneen_US
dc.date.accessioned2023-06-10T06:31:33Z
dc.date.available2023-06-10T06:31:33Z
dc.date.issued2023
dc.description.abstractIn the modern web experience, users interact with various types of recommender systems. In this literature study, we investigate the role of interaction in explainable recommender systems using 27 relevant papers from recommender systems, humancomputer interaction, and visualization fields. We structure interaction approaches into 1) the task, 2) the interaction intent, 3) the interaction technique, and 4) the interaction effect on explainable recommender systems. We present a preliminary interaction taxonomy for designers and developers to improve the interaction design of explainable recommender systems. Findings based on exploiting the descriptive power of the taxonomy emphasize the importance of interaction in creating effective and user-friendly explainable recommender systems.en_US
dc.description.seriesinformationEuroVis 2023 - Posters
dc.identifier.doi10.2312/evp.20231062
dc.identifier.isbn978-3-03868-220-2
dc.identifier.pages37-39
dc.identifier.pages3 pages
dc.identifier.urihttps://doi.org/10.2312/evp.20231062
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evp20231062
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleInteraction Tasks for Explainable Recommender Systemsen_US
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