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Title:Student perspectives on personalized account-based recommender systems in libraries
Author(s):Hahn, James F.
recommender systems
academic libraries
research libraries
student interviews
interdisciplinary research
Abstract:A personalized account-based recommender was developed in the University of Illinois Library's mobile app interface. The recommender system (RS) was derived from data mining topic clusters of items that are checked out together. Using the library mobile RS as a prompt to understand student preferences for personalized account-based RS, structured interviews were undertaken and analyzed thematically to determine RS features and functionality desired. In the interviews, students described their perceptions of RS, together with features and functionality desired. Students indicated that they desired data stewardship and sharing levels, which provided valuable input into matters of system transparency pertaining to recommendations derived algorithmically. An unexpected finding from students was growing unease with aspects of surveillance capitalism. Academic library recommenders can distinguish themselves from commercial recommenders in several ways, including increased transparency beyond what is available in commercial systems, and by attending to student privacy and data retention as a system design issue.
Issue Date:2019-06-12
Citation Info:Hahn, J. (2019). “Student perspectives on personalized account-based recommender systems in libraries,” Discovery and Online Search, Part One: Drivers of Change in Online Search, NISO Online Webinar: June 12.
Genre:Presentation / Lecture / Speech
Rights Information:© Jim Hahn 2019
Date Available in IDEALS:2019-06-12

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