User Modeling and User-Adapted Interaction

, Volume 27, Issue 3–5, pp 393–444 | Cite as

A systematic review and taxonomy of explanations in decision support and recommender systems

  • Ingrid NunesEmail author
  • Dietmar Jannach


With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems. A key requirement for the success and adoption of such systems is that users must trust system choices or even fully automated decisions. To achieve this, explanation facilities have been widely investigated as a means of establishing trust in these systems since the early years of expert systems. With today’s increasingly sophisticated machine learning algorithms, new challenges in the context of explanations, accountability, and trust towards such systems constantly arise. In this work, we systematically review the literature on explanations in advice-giving systems. This is a family of systems that includes recommender systems, which is one of the most successful classes of advice-giving software in practice. We investigate the purposes of explanations as well as how they are generated, presented to users, and evaluated. As a result, we derive a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems. The taxonomy includes a variety of different facets, such as explanation objective, responsiveness, content and presentation. Moreover, we identified several challenges that remain unaddressed so far, for example related to fine-grained issues associated with the presentation of explanations and how explanation facilities are evaluated.


Explanation Decision support system Recommender system Expert system Knowledge-based system Systematic review Machine learning Trust Artificial intelligence 



The authors would like to thank Michael Jugovac for carefully proofreading this paper. Ingrid Nunes also would like to thank for research grants CNPq ref. 303232/2015-3, CAPES ref. 7619-15-4, and Alexander von Humboldt, ref. BRA 1184533 HFSTCAPES-P.


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© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Universidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
  2. 2.TU DortmundDortmundGermany

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