Loepp, Benedikt; Barbu, Catalin-Mihai; Ziegler, Jürgen:
Interactive Recommending : Framework, State of Research and Future Challenges
In: EnCHIReS 2016 : Engineering Computer-Human Interaction in Recommender Systems : Proceedings of the Workshop on Engineering Computer-Human Interaction in Recommender Systems co-located with the 8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2016) - Workshop on Engineering Computer-Human Interaction in Recommender Systems, EnCHIReS 2016, 21. Juni 2016, Bruxelles, Belgium - 2016 - (CEUR workshop proceedings ; 1705), pp. 3 - 13
2016book article/chapter in ProceedingsOA Gold
Computer ScienceFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Informatik » Interaktive Systeme / Interaktionsdesign
Title in English:
Interactive Recommending : Framework, State of Research and Future Challenges
Author:
Loepp, BenediktLSF; Barbu, Catalin-MihaiLSF; Ziegler, JürgenLSF
Open Access?
OA Gold
WWW URL
Language of text
English
Keyword, Topic:
Recommender Systems ; nteractive Recommending ; Models ; User Experience ; User Interfaces ; Survey

Abstract in English:

In this paper, we present a framework describing the various aspects of recommender systems that can serve for empowering users by giving them more interactive control and transparency in the recommendation process. While conventional recommenders mostly operate like black boxes that cannot be influenced by the user, we identify four aspects properly connected with the recommendation algorithm—namely input data, user model, external con-text model and presentation—as essential points in which a system may be enhanced by additional interaction possibilities. In light of this framework, we take a closer look at prior and present solutions to integrate recommender systems with more interactivity and describe future research challenges. Regarding these challenges, we especially focus on experiences gained in our own work and outline future research we have planned in the area of interactive recommending.