Interaction design in a mobile food recommender system

Mehdi Elahi, Mouzhi Ge, Francesco Ricci, Ignacio Fernández-Tobias, Shlomo Berkovsky, Massimo David

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

14 Citations (Scopus)

Abstract

One of the most important steps in building a recommender system is the interaction design process, which defines how the recommender system interacts with a user. It also shapes the experience the user gets, from the point she registers and provides her preferences to the system, to the point she receives recommendations generated by the system. A proper interaction design may improve user experience and hence may result in higher usability of the system, as well as, in higher satisfaction.
In this paper, we focus on the interaction design of a mobile food recommender system that, through a novel interaction process, elicits users’ long-term and short-term preferences for recipes. User’s long-term preferences are captured
by asking the user to rate and tag familiar recipes, while for collecting the short-term preferences, the user is asked to select the ingredients she would like to include in the recipe to be prepared. Based on the combined exploitation of both
types of preferences, a set of personalized recommendations is generated. We conducted a user study measuring the usability of the proposed interaction. The results of the study show that the majority of users rates the quality of the recommendations high and the system achieves usability scores above the standard benchmark.
Original languageEnglish
Title of host publicationInterfaces and Human Decision Making for Recommender Systems
Subtitle of host publicationProceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2015)
EditorsJohn O'Donovan, Alexander Felfernig, Nava Tintarev, Peter Brusilovsky, Giovanni Semeraro, Pasquale Lops
PublisherCEUR Workshop Proceedings
Pages49-52
Number of pages4
Volume1438
Publication statusPublished - 2015
Externally publishedYes
Event9th ACM Conference on Recommender Systems, RecSys 2015 - Vienna, Austria
Duration: 16 Sep 201520 Sep 2015

Publication series

NameCEUR Workshop Proceedings
PublisherRWTH Aachen University
ISSN (Print)1613-0073

Conference

Conference9th ACM Conference on Recommender Systems, RecSys 2015
CountryAustria
CityVienna
Period16/09/1520/09/15

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