What are the best ways to present recommendations to users? A systematic mapping study
DOI:
https://doi.org/10.5753/isys.2019.780Keywords:
Recommender systems, Visualization, User experience, Human-Computer InteractionAbstract
Recommender systems use information about the user to generate a set of personalized items as a suggestion and are applied in contexts where it exists an overload of content available to the user. The way these recommendations are viewed is now the focus of recent studies based on the need to improve the user experience with recommender systems. This paper presents a Systematic Mapping Study aiming to identify the best ways to present recommendations to users. A total of 434 papers were identified, of which 27 were selected for further analysis. The results point to a tendency towards self-explanatory and interactive interfaces.
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References
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O’Donovan, J., Smyth, B., Gretarsson, B., Bostandjiev, S., and Ho¨llerer, T. (2008). Pe- erchooser: Visual interactive recommendation. In Proceedings of the SIGCHI Con- ference on Human Factors in Computing Systems, CHI ’08, pages 1085–1088, New York, NY, USA. ACM.
Parra, D. and Brusilovsky, P. (2013). A field study of a visual controllable talk recommen- der. In Proceedings of the 2013 Chilean Conference on Human - Computer Interaction, ChileCHI ’13, pages 56–59, New York, NY, USA. ACM.
Parra, D. and Brusilovsky, P. (2015). User-controllable personalization: A case study with setfusion. International Journal of Human-Computer Studies, 78:43 – 67.
Parra, D., Brusilovsky, P., and Trattner, C. (2014). See what you want to see: Visual user- driven approach for hybrid recommendation. In Proceedings of the 19th International Conference on Intelligent User Interfaces, IUI ’14, pages 235–240, New York, NY, USA. ACM.
Peng, T. and Jinqi, P. (2017). A recommendation system for collaborative visualization platforms. In 2017 5th International Conference on Enterprise Systems (ES), pages 58–61.
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. In Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering, EASE’08, pages 68–77, Swindon, UK. BCS Learning & Development Ltd.
Petersen, K., Vakkalanka, S., and Kuzniarz, L. (2015). Guidelines for conducting syste- matic mapping studies in software engineering: An update. Information and Software Technology, 64:1 – 18.
Piazza, A., Zagel, C., Huber, S., Hille, M., and Bodendorf, F. (2015). Outfit browser aˆ“ an image-data-driven user interface for self-service systems in fashion stores. Proce- dia Manufacturing, 3:3521 – 3528. 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015.
Pu, P., Chen, L., and Hu, R. (2012). Evaluating recommender systems from the user’s perspective: survey of the state of the art. User Modeling and User-Adapted Interac- tion, 22(4):317–355.
Ricci, F., Rokach, L., and Shapira, B. (2011). Introduction to Recommender Systems Handbook, pages 1–35. Springer US, Boston, MA.
Ricci, F., Rokach, L., and Shapira, B. (2015). Recommender Systems Handbook. Springer US.
Saito, Y. and Itoh, T. (2011). Musicube: A visual music recommendation system featuring interactive evolutionary computing. In Proceedings of the 2011 Visual Information Communication - International Symposium, VINCI ’11, pages 5:1–5:6, New York, NY, USA. ACM.
Schedl, M., Melenhorst, M., Liem, C. C. S., Martorell, A., Mayor, O., and Tkalcˇicˇ, M. (2016). A personality-based adaptive system for visualizing classical music perfor- mances. In Proceedings of the 7th International Conference on Multimedia Systems, MMSys ’16, pages 15:1–15:7, New York, NY, USA. ACM.
Teófilo, L. F. and Silva, P. B. (2011). Integrating simple recommendation systems on digital tv widget applications. In 6th Iberian Conference on Information Systems and Technologies (CISTI 2011), pages 1–6.
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Tsai, C.-H. and Brusilovsky, P. (2017a). Leveraging interfaces to improve recommenda- tion diversity. In Adjunct Publication of the 25th Conference on User Modeling, Adap- tation and Personalization, UMAP ’17, pages 65–70, New York, NY, USA. ACM.
Tsai, C.-H. and Brusilovsky, P. (2017b). Providing control and transparency in a social recommender system for academic conferences. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, UMAP ’17, pages 313–317, New York, NY, USA. ACM.
Vartak, M., Huang, S., Siddiqui, T., Madden, S., and Parameswaran, A. (2017). Towards visualization recommendation systems. SIGMOD Rec., 45(4):34–39.
Verbert, K., Brusilovsky, P., Wongchokprasitti, C., Parra, D., and Cardoso, B. (2017). Supporting conference attendees with visual decision making interfaces. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces Companion, IUI ’17 Companion, pages 161–164, New York, NY, USA. ACM.
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Verbert, K., Parra, D., Brusilovsky, P., and Duval, E. (2013). Visualizing recommenda- tions to support exploration, transparency and controllability. In Proceedings of the 2013 International Conference on Intelligent User Interfaces, IUI ’13, pages 351–362, New York, NY, USA. ACM.
Waldner, W. and Vassileva, J. (2014). Emphasize, don’t filter!: Displaying recommenda- tions in twitter timelines. In Proceedings of the 8th ACM Conference on Recommender Systems, RecSys ’14, pages 313–316, New York, NY, USA. ACM.
Wang, W., Zhang, G., and Lu, J. (2017). Hierarchy visualization for group recommender systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, pages 1–12.
Zhang, J., Jones, N., and Pu, P. (2008). A visual interface for critiquing-based recommen- der systems. In Proceedings of the 9th ACM Conference on Electronic Commerce, EC ’08, pages 230–239, New York, NY, USA. ACM.
Avazpour, I. and Grundy, J. (2017). Insights into visualizing trajectory recommendation rankings. In Proceedings of the Australasian Computer Science Week Multiconference, ACSW ’17, pages 10:1–10:4, New York, NY, USA. ACM.
Buchinger, D., Cavalcanti, G., and Hounsell, M. (2014). Mecanismos de busca acadeˆmica: uma ana´lise quantitativa. Revista Brasileira de Computac¸a˜o Aplicada, 6(1):108–120.
Calero Valdez, A., Ziefle, M., and Verbert, K. (2016). Hci for recommender systems: The past, the present and the future. In Proceedings of the 10th ACM Conference on Recommender Systems, RecSys ’16, pages 123–126, New York, NY, USA. ACM.
Du, F., Plaisant, C., Spring, N., and Shneiderman, B. (2016). Eventaction: Visual analy- tics for temporal event sequence recommendation. In 2016 IEEE Conference on Visual Analytics Science and Technology (VAST), pages 61–70.
Gedikli, F., Jannach, D., and Ge, M. (2014). How should i explain? a comparison of dif- ferent explanation types for recommender systems. International Journal of Human- Computer Studies, 72(4):367 – 382.
Gretarsson, B., O’Donovan, J., Bostandjiev, S., Hall, C., and Ho¨llererk, T. (2010). Smallworlds: Visualizing social recommendations. In Proceedings of the 12th Eu- rographics / IEEE - VGTC Conference on Visualization, EuroVis’10, pages 833–842, Chichester, UK. The Eurographs Association & John Wiley & Sons, Ltd.
Holm, J. and Siirtola, H. (2012). A comparison of methods for visualizing musical genres. In 2012 16th International Conference on Information Visualisation, pages 636–645.
Huaiqing, H., Hongrui, D., and Haohan, L. (2016). Overview and investigation of the visualization methods in recommendation systems. In 2016 8th International Con- ference on Computational Intelligence and Communication Networks (CICN), pages 601–605.
Jagadeesh, V., Piramuthu, R., Bhardwaj, A., Di, W., and Sundaresan, N. (2014). Large scale visual recommendations from street fashion images. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14, pages 1925–1934, New York, NY, USA. ACM.
Jannach, D., Zanker, M., Felfernig, A., and Friedrich, G. (2010). Recommender Systems: An Introduction. Cambridge University Press.
Kanchana, W. A. D., Madushanka, G. D. L., Maduranga, H. P., Udayanga, M. D. M., Meedeniya, D. A., and Perera, I. (2017). Semi-automated recommendation platform for data visualization: Roopana. In 2017 Moratuwa Engineering Research Conference (MERCon), pages 117–122.
Katarya, R., Jain, I., and Hasija, H. (2014). An interactive interface for instilling trust and providing diverse recommendations. In 2014 International Conference on Computer and Communication Technology (ICCCT), pages 17–22.
Kouki, P., Schaffer, J., Pujara, J., O’Donovan, J., and Getoor, L. (2017). User prefe- rences for hybrid explanations. In Proceedings of the Eleventh ACM Conference on Recommender Systems, RecSys ’17, pages 84–88, New York, NY, USA. ACM.
Kunkel, J., Loepp, B., and Ziegler, J. (2017). A 3d item space visualization for presenting and manipulating user preferences in collaborative filtering. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces, IUI ’17, pages 3–15, New York, NY, USA. ACM.
Nagulendra, S. and Vassileva, J. (2014). Understanding and controlling the filter bubble through interactive visualization: A user study. In Proceedings of the 25th ACM Con- ference on Hypertext and Social Media, HT ’14, pages 107–115, New York, NY, USA. ACM.
O’Donovan, J., Gretarsson, B., Bostandjiev, S., Hollerer, T., and Smyth, B. (2009). A visual interface for social information filtering. In 2009 International Conference on Computational Science and Engineering, volume 4, pages 74–81.
O’Donovan, J., Smyth, B., Gretarsson, B., Bostandjiev, S., and Ho¨llerer, T. (2008). Pe- erchooser: Visual interactive recommendation. In Proceedings of the SIGCHI Con- ference on Human Factors in Computing Systems, CHI ’08, pages 1085–1088, New York, NY, USA. ACM.
Parra, D. and Brusilovsky, P. (2013). A field study of a visual controllable talk recommen- der. In Proceedings of the 2013 Chilean Conference on Human - Computer Interaction, ChileCHI ’13, pages 56–59, New York, NY, USA. ACM.
Parra, D. and Brusilovsky, P. (2015). User-controllable personalization: A case study with setfusion. International Journal of Human-Computer Studies, 78:43 – 67.
Parra, D., Brusilovsky, P., and Trattner, C. (2014). See what you want to see: Visual user- driven approach for hybrid recommendation. In Proceedings of the 19th International Conference on Intelligent User Interfaces, IUI ’14, pages 235–240, New York, NY, USA. ACM.
Peng, T. and Jinqi, P. (2017). A recommendation system for collaborative visualization platforms. In 2017 5th International Conference on Enterprise Systems (ES), pages 58–61.
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. In Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering, EASE’08, pages 68–77, Swindon, UK. BCS Learning & Development Ltd.
Petersen, K., Vakkalanka, S., and Kuzniarz, L. (2015). Guidelines for conducting syste- matic mapping studies in software engineering: An update. Information and Software Technology, 64:1 – 18.
Piazza, A., Zagel, C., Huber, S., Hille, M., and Bodendorf, F. (2015). Outfit browser aˆ“ an image-data-driven user interface for self-service systems in fashion stores. Proce- dia Manufacturing, 3:3521 – 3528. 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015.
Pu, P., Chen, L., and Hu, R. (2012). Evaluating recommender systems from the user’s perspective: survey of the state of the art. User Modeling and User-Adapted Interac- tion, 22(4):317–355.
Ricci, F., Rokach, L., and Shapira, B. (2011). Introduction to Recommender Systems Handbook, pages 1–35. Springer US, Boston, MA.
Ricci, F., Rokach, L., and Shapira, B. (2015). Recommender Systems Handbook. Springer US.
Saito, Y. and Itoh, T. (2011). Musicube: A visual music recommendation system featuring interactive evolutionary computing. In Proceedings of the 2011 Visual Information Communication - International Symposium, VINCI ’11, pages 5:1–5:6, New York, NY, USA. ACM.
Schedl, M., Melenhorst, M., Liem, C. C. S., Martorell, A., Mayor, O., and Tkalcˇicˇ, M. (2016). A personality-based adaptive system for visualizing classical music perfor- mances. In Proceedings of the 7th International Conference on Multimedia Systems, MMSys ’16, pages 15:1–15:7, New York, NY, USA. ACM.
Teófilo, L. F. and Silva, P. B. (2011). Integrating simple recommendation systems on digital tv widget applications. In 6th Iberian Conference on Information Systems and Technologies (CISTI 2011), pages 1–6.
Tsai, C.-H. (2017). An interactive and interpretable interface for diversity in recommender systems. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces Companion, IUI ’17 Companion, pages 225–228, New York, NY, USA. ACM.
Tsai, C.-H. and Brusilovsky, P. (2017a). Leveraging interfaces to improve recommenda- tion diversity. In Adjunct Publication of the 25th Conference on User Modeling, Adap- tation and Personalization, UMAP ’17, pages 65–70, New York, NY, USA. ACM.
Tsai, C.-H. and Brusilovsky, P. (2017b). Providing control and transparency in a social recommender system for academic conferences. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, UMAP ’17, pages 313–317, New York, NY, USA. ACM.
Vartak, M., Huang, S., Siddiqui, T., Madden, S., and Parameswaran, A. (2017). Towards visualization recommendation systems. SIGMOD Rec., 45(4):34–39.
Verbert, K., Brusilovsky, P., Wongchokprasitti, C., Parra, D., and Cardoso, B. (2017). Supporting conference attendees with visual decision making interfaces. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces Companion, IUI ’17 Companion, pages 161–164, New York, NY, USA. ACM.
Verbert, K., Parra, D., and Brusilovsky, P. (2016). Agents vs. users: Visual recommendation of research talks with multiple dimension of relevance. ACM Trans. Interact. Intell. Syst., 6(2):11:1–11:42.
Verbert, K., Parra, D., Brusilovsky, P., and Duval, E. (2013). Visualizing recommenda- tions to support exploration, transparency and controllability. In Proceedings of the 2013 International Conference on Intelligent User Interfaces, IUI ’13, pages 351–362, New York, NY, USA. ACM.
Waldner, W. and Vassileva, J. (2014). Emphasize, don’t filter!: Displaying recommenda- tions in twitter timelines. In Proceedings of the 8th ACM Conference on Recommender Systems, RecSys ’14, pages 313–316, New York, NY, USA. ACM.
Wang, W., Zhang, G., and Lu, J. (2017). Hierarchy visualization for group recommender systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, pages 1–12.
Zhang, J., Jones, N., and Pu, P. (2008). A visual interface for critiquing-based recommen- der systems. In Proceedings of the 9th ACM Conference on Electronic Commerce, EC ’08, pages 230–239, New York, NY, USA. ACM.
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Published
2020-04-24
How to Cite
de Borba, C. S., & Gasparini, I. (2020). What are the best ways to present recommendations to users? A systematic mapping study. ISys - Brazilian Journal of Information Systems, 12(4), 36–63. https://doi.org/10.5753/isys.2019.780
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