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Title: Recommender Systems for Self-Actualization
Every day, we are confronted with an abundance of decisions that require us to choose from a seemingly endless number of choice options. Recommender systems are supposed to help us deal with this formidable task, but some scholars claim that these systems instead put us inside a "Filter Bubble" that severely limits our perspectives. This paper presents a new direction for recommender systems research with the main goal of supporting users in developing, exploring, and understanding their unique personal preferences.  more » « less
Award ID(s):
1565809
NSF-PAR ID:
10024867
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Proceedings of the 10th ACM Conference on Recommender Systems
Page Range / eLocation ID:
11 to 14
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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