This paper introduces a community-based approach to facilitate the generation of high-quality recommendations by leveraging the preferences of communities of similar users in preference networks. The proposed approach combines the idea of traditional recommendation systems and identification of network structures to explore context specific inter-personalised trust relationships among users. From the experimental results, we claim that the proposed approach can provide more accurate recommendations to individuals in a preference network.
History
Publication title
29th Australasian Joint Conference on Artificial Intelligence (AI 2016): Advances in Artificial Intelligence. Lecture Notes in Computer Science, volume 9992
Volume
9992
Editors
B Kang and Q Bai
Pagination
573-584
ISBN
9783319501260
Department/School
School of Information and Communication Technology
Publisher
Springer
Place of publication
New York, United States
Event title
29th Australasian Joint Conference on Artificial Intelligence (AI 2016): Advances in Artificial Intelligence