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Title:A Personalized Account-Based Recommender within the University Library’s Mobile App Interface
Author(s):Hahn, James F.
Subject(s):Machine Learning
IMLS
personalization
recommender system
Weka
Abstract:With funding from the University of Illinois Campus Research Board, researchers developed a personalized account-based recommender within the university library’s mobile app interface. The recommender system (RS) is derived from two key data sources 1) data mining of item topic clusters checked out together in the university library and 2) consequent topics from data mining paired with filtered searches of the library catalog.
Issue Date:2019-03-11
Citation Info:Hahn, J. (2019). “A Personalized Account-Based Recommender within the University Library’s Mobile App Interface,” IMLS Workshop on Discovery in Cross-Disciplinary Research/Machine Learning, Notre Dame, IN: March 11.
Genre:Presentation / Lecture / Speech
Type:Text
Image
Language:English
URI:http://hdl.handle.net/2142/103166
Sponsor:University of Illinois Campus Research Board (RB16001)
Rights Information:© Jim Hahn 2019
Date Available in IDEALS:2019-03-12


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