Analysing recommender systems impact on users’ choices
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In this paper we introduce a novel model for simulating the choice making procedure of users under the influence of a Recommender System (RS). Our model leverages the knowledge of users’ preferences and simulates repeated choices. We investigate the evolution of these simulated choices in the presence of different RSs and analyse their impact on the Gini index, as indicator of choice diversity. Running the simulation we have observed that all the considered RSs increase the awareness of the users about the items while they affect the aggregated choice diversity differently.
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Tkalcic M; Kosir A; Tasic J (CEUR-WS.org, 2011)Recommender systems have traditionally relied on data-centric descriptors for content and user modeling. In recent years we have witnessed an increasing number of attempts to use emotions in di?erent ways to improve the ...
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Proceedings of the Workshop on Location-Aware Recommendations (LocalRec 2015) co-located with the 9th ACM Conference on Recommender Systems (RecSys 2015) Bouros P; Lathia N; Renz M; Ricci F; Sacharidis D (CEUR, 2015)