Visualising Module Dependencies in Academic Recommendations
|Title:||Visualising Module Dependencies in Academic Recommendations||Authors:||Hagemann, Nina; O'Mahony, Michael P.; Smyth, Barry||Permanent link:||http://hdl.handle.net/10197/10796||Date:||20-Mar-2019||Online since:||2019-06-12T11:44:26Z||Abstract:||Starting their academic career can be overwhelming for many young people. Students are often presented with a variety of options within their programmes of study and making appropriate and informed decisions can be a challenge. Compared to many other areas in our every day life, recommender systems remain under used in the academic setting. In this part of our research we use non-negative matrix factorisation to identify dependencies between modules, visualise sequential recommendations, and bring structure and clarity into the academic module space.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||ACM||Start page:||77||End page:||78||Copyright (published version):||2019 Association for Computing Machinery||Keywords:||Recommender systems; Non-negative matrix factorisation; Academic advising||DOI:||10.1145/3308557.3308701||Other versions:||https://iui.acm.org/2019/||Language:||en||Status of Item:||Peer reviewed||Is part of:||IUI '19 Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion||Conference Details:||ACM IUI 2019: 24th International Conference on Intelligent User Interfaces, Los Angeles, USA, 16-20 March 2019||ISBN:||978-1-4503-6673-1|
|Appears in Collections:||Insight Research Collection|
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