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Mining context specific inter-personalised trust for recommendation generation in preference networks

Citation

Bai, Q and Li, W and Jiang, J, Mining context specific inter-personalised trust for recommendation generation in preference networks, 29th Australasian Joint Conference on Artificial Intelligence (AI 2016): Advances in Artificial Intelligence. Lecture Notes in Computer Science, volume 9992, 5-8 December 2016, Hobart, Tasmania, pp. 573-584. ISBN 9783319501260 (2016) [Refereed Conference Paper]


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Copyright Statement

Copyright 2016 Springer

DOI: doi:10.1007/978-3-319-50127-7_51

Abstract

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.

Item Details

Item Type:Refereed Conference Paper
Keywords:community detection, preference network, recommender system
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140682
Year Published:2016
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-10-29
Downloads:4 View Download Statistics

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