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A systematic mapping on adaptive recommender approaches for ubiquitous environments

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Abstract

Recommender systems were first conceived to provide suggestions of interesting items to users. The evolution of such systems provided an understanding that a recommender system is currently used to diverse objectives. One of the current challenges in the field is to have approaches of recommendation that go beyond accuracy metrics. Since it is a very recent interest of the community, this review, also characterized as an exploratory search, provides an overview of the techniques in the area that tries to look beyond accuracy. More specifically, one of the characteristics that would provide such evolution to these systems is the adaptation. This review is then performed to find the existence and characteristics of such approaches. Of the total 438 papers returned in the submission of the search string, 57 papers were analyzed after two filtering processes. The papers have shown that the area is little explored and one of the reasons is the challenge to validate non-accuracy characteristics in such approaches.

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Acknowledgements

The authors would like to thank CNPq and CAPES, Brazil.

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Authors and Affiliations

  1. INF-UFRGS, Porto Alegre, RS, Brazil

    Guilherme M. Machado, Vinicius Maran, Lorayne P. Dornelles, Lucinéia H. Thom & José Palazzo M. de Oliveira

  2. UDESC, Joinville, SC, Brazil

    Isabela Gasparini

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  1. Guilherme M. Machado
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  2. Vinicius Maran
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  3. Lorayne P. Dornelles
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Correspondence to Guilherme M. Machado.

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Machado, G.M., Maran, V., Dornelles, L.P. et al. A systematic mapping on adaptive recommender approaches for ubiquitous environments. Computing 100, 183–209 (2018). https://doi.org/10.1007/s00607-017-0572-7

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