Algorithms Aside: Recommendation as the Lens of Life

Motajcsek, T. et al. (2016) Algorithms Aside: Recommendation as the Lens of Life. In: RecSYS 2016: 10th ACM Conference on Recommender Systems, Boston, MA, USA, 15-19 Sept. 2016, pp. 215-219. ISBN 9781450340359 (doi:10.1145/2959100.2959164)

120471.pdf - Accepted Version



In this position paper, we take the experimental approach of putting algorithms aside, and reflect on what recommenders would be for people if they were not tied to technology. By looking at some of the shortcomings that current recommenders have fallen into and discussing their limitations from a human point of view, we ask the question: if freed from all limitations, what should, and what could, RecSys be? We then turn to the idea that life itself is the best recommender system, and that people themselves are the query. By looking at how life brings people in contact with options that suit their needs or match their preferences, we hope to shed further light on what current RecSys could be doing better. Finally, we look at the forms that RecSys could take in the future. By formulating our vision beyond the reach of usual considerations and current limitations, including business models, algorithms, data sets, and evaluation methodologies, we attempt to arrive at fresh conclusions that may inspire the next steps taken by the community of researchers working on RecSys.

Item Type:Conference Proceedings
Additional Information:The work leading to this paper has received funding from the European Union’s Seventh Framework Programme (FP7/2007- 2013) under CrowdRec Grant Agreement n◦ 610594.
Glasgow Author(s) Enlighten ID:Hopfgartner, Dr Frank
Authors: Motajcsek, T., Le Moine, J.-Y., Cremonesi, P., Dobrajs, K., Hopfgartner, F., Garzotto, F., Göker, A., Kohlsdorf, D., Demetriou, A., Larson, M., Lommatzsch, A., Malagoli, D., Thuy, N. N., Novak, J., Ricci, F., Scriminaci, M., Tikk, D., Tkalcic, M., Zacchi, A., and Alonso, O.
College/School:College of Arts > School of Humanities > Information Studies
Copyright Holders:Copyright © 2016 ACM
First Published:First published in Proceedings of the 10th ACM Conference on Recommender Systems: 215-219
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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