62,751 research outputs found
Visualization for Recommendation Explainability: A Survey and New Perspectives
Providing system-generated explanations for recommendations represents an
important step towards transparent and trustworthy recommender systems.
Explainable recommender systems provide a human-understandable rationale for
their outputs. Over the last two decades, explainable recommendation has
attracted much attention in the recommender systems research community. This
paper aims to provide a comprehensive review of research efforts on visual
explanation in recommender systems. More concretely, we systematically review
the literature on explanations in recommender systems based on four dimensions,
namely explanation goal, explanation scope, explanation style, and explanation
format. Recognizing the importance of visualization, we approach the
recommender system literature from the angle of explanatory visualizations,
that is using visualizations as a display style of explanation. As a result, we
derive a set of guidelines that might be constructive for designing explanatory
visualizations in recommender systems and identify perspectives for future work
in this field. The aim of this review is to help recommendation researchers and
practitioners better understand the potential of visually explainable
recommendation research and to support them in the systematic design of visual
explanations in current and future recommender systems.Comment: Updated version Nov. 2023, 36 page
On Regulatory and Organizational Constraints in Visualization Design and Evaluation
Problem-based visualization research provides explicit guidance toward
identifying and designing for the needs of users, but absent is more concrete
guidance toward factors external to a user's needs that also have implications
for visualization design and evaluation. This lack of more explicit guidance
can leave visualization researchers and practitioners vulnerable to unforeseen
constraints beyond the user's needs that can affect the validity of
evaluations, or even lead to the premature termination of a project. Here we
explore two types of external constraints in depth, regulatory and
organizational constraints, and describe how these constraints impact
visualization design and evaluation. By borrowing from techniques in software
development, project management, and visualization research we recommend
strategies for identifying, mitigating, and evaluating these external
constraints through a design study methodology. Finally, we present an
application of those recommendations in a healthcare case study. We argue that
by explicitly incorporating external constraints into visualization design and
evaluation, researchers and practitioners can improve the utility and validity
of their visualization solution and improve the likelihood of successful
collaborations with industries where external constraints are more present.Comment: 9 pages, 2 figures, presented at BELIV workshop associated with IEEE
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