Hungerbühler S, Jóhnsson HP, Lisowski G, Rapp M (2019)
Publication Type: Conference contribution
Publication year: 2019
Publisher: Springer Verlag
Book Volume: 11667 LNCS
Pages Range: 62-78
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN: 9783662596197
DOI: 10.1007/978-3-662-59620-3_4
We tackle the practical problem of finding a good rule to recommend a collective set of news items to a group of media consumers with possibly very disparate individual interest in the available items. For our analysis, we adapt a formal framework from voting theory in Computational Social Choice to the media setting in order to compare the performance of five recommendation rules with respect to several desirable properties of recommendation sets. Through simulations, we find that polarization of the audience limits how well these rules can perform in general. On the other hand, greater diversity or universality can be achieved at only low cost in utility.
APA:
Hungerbühler, S., Jóhnsson, H.P., Lisowski, G., & Rapp, M. (2019). Social Choice and the Problem of Recommending Essential Readings. In Eric Pacuit, Jennifer Sikos (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 62-78). Sofia, BG: Springer Verlag.
MLA:
Hungerbühler, Silvan, et al. "Social Choice and the Problem of Recommending Essential Readings." Proceedings of the 30th European Summer School in Logic, Language and Information, ESSLLI 2018, Sofia Ed. Eric Pacuit, Jennifer Sikos, Springer Verlag, 2019. 62-78.
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