Journal's Facebook pageTowards Understandable Personalized Recommendations: Hybrid Explanations
- Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies
Ilkovicova 2, 841 04 Bratislava, Slovakia
{name.surname}@stuba.sk
Abstract
Nowadays, personalized recommendations are widely used and popular. There are a lot of systems in various fields, which use recommendations for different purposes. One of the basic problems is the distrust of users of recommended systems. Users often consider the recommendations as an intrusion of their privacy. Therefore, it is important to make recommendations transparent and understandable to users. To address these problems, we propose a novel hybrid method of personalized explanation of recommendations. Our method is independent of recommendation technique and combines basic explanation styles to provide the appropriate type of personalized explanation to each user. We conducted several online experiments in the news domain. Obtained results clearly show that the proposed personalized hybrid explanation approach improves the users’ attitude towards the recommender, moreover, we have observed the increase of recommendation precision.
Key words
recommendations explanation, eye-tracking, collaborative filtering, personalized recommendation
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS171217012S
Publication information
Volume 16, Issue 1 (January 2019)
Year of Publication: 2019
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
Full text
Available in PDF
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How to cite
Svrcek, M., Kompan, M., Bielikova, M.: Towards Understandable Personalized Recommendations: Hybrid Explanations. Computer Science and Information Systems, Vol. 16, No. 1, 179-203. (2019), https://doi.org/10.2298/CSIS171217012S
