Investigating the use of association rules in improving recommender systems
Shaw, Gavin, Xu, Yue, & Geva, Shlomo (2009) Investigating the use of association rules in improving recommender systems. In ADCS 2009 : HCSNet Summerfest 09, 14th Australasian Document Computing Symposium, 30 Nov. - 4 Dec., 2009, University of New South Wales, Sydney, Australia.
Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus when there is not sufficient knowledge on a user it is difficult for a recommender system to make quality recommendations. This problem is often referred to as the cold-start problem. Here we investigate whether association rules can be used as a source of information to expand a user profile and thus avoid this problem, leading to improved recommendations to users. Our pilot study shows that indeed it is possible to use association rules to improve the performance of a recommender system. This we believe can lead to further work in utilising appropriate association rules to lessen the impact of the cold-start problem.
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|Item Type:||Conference Item (Poster)|
|Keywords:||Information Retrieval, Personalised Documents, Recommender Systems, Association Rules|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems not elsewhere classified (080699)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > School of Information Technology
|Copyright Owner:||Copyright 2009 please contact the authors|
|Deposited On:||20 Jan 2010 09:56|
|Last Modified:||01 Mar 2012 00:12|
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