Browse University Library by Subject "personalization"
Now showing items 1-8 of 8
(Emerald Publishing Limited, 2018)This paper aims to introduce a machine learning-based “My Account” recommender for implementation in open discovery environments such as VuFind among others. The approach to implementing machine learning-based personalized ...
(Code4Lib, 2018-11-08)The Minrva project team, a software development research group based at the University of Illinois Library, developed a data-focused recommender system to participate in the creative track of the 2018 ACM RecSys Challenge, ...
(ACM, 2019-05-13)A library account-based recommender system was developed using machine learning processing over transactional data of 383,828 check-outs sourced from a large multi-unit research library. The machine learning process utilized ...
(2019-03-11)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 ...
application/vnd.openxmlformats-officedocument.presentationml.presentationMicrosoft PowerPoint 2007 (7MB)
Poster for: Approaches to systematic transaction data reuse: machine learning support of information discovery (F1000Research, 2019-05-13)The purpose of this poster is to detail approaches in systematic transactional data reuse using machine learning and network science visualization methods. Preliminary machine learning workflows were undertaken in WEKA and ...
(NISO, 2019-06-12)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 ...
(Coalition for Networked Information (CNI), 2019-04-08)With research funding from the University of Illinois Campus Research Board, a personalized account-based recommender was developed in the University Library's mobile app interface. The recommender system (RS) was derived ...
(ACRL, 2019-04-11)This research is focused on understanding user preferences for "my account"-based recommendations of library content. By interviewing users we have explored user attitudes about three areas of recommendation services; ...