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Effect of influential users on recommendation

Oshodin, Eseosa; Chiclana, Francisco

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Authors

Francisco Chiclana



Abstract

Relevant information stored in boundless pool of data source are required for the recommendation provided for users in recommender systems. Current recommender systems still suffer from inaccurate or erroneous predictions for users. This may be due to lack of consensus between users who provide different opinions on items after purchase. However, it is possible that this problem might be due to the users having no/few knowledge on the items or they might have had diverse reasons for previous purchase of the items. Therefore, they decide to either provide untruthful opinions on the items or to not even provide their opinions on the items. This demo paper presents a proposed approach to recommendation, where trust information from the social network can be used to motivate or influence users to contribute their opinions for future recommendation. A new trust metric based on trust features such as familiarity and experience value will be used to identify influential users who will control information flow and motivate the members in their community.

Citation

Oshodin, E., & Chiclana, F. (2015). Effect of influential users on recommendation. In 2015 SAI Intelligent Systems Conference (IntelliSys) (731-732). https://doi.org/10.1109/IntelliSys.2015.7361221

Conference Name 2015 SAI Intelligent Systems Conference (IntelliSys)
Conference Location London, United Kingdom
Start Date Nov 10, 2015
End Date Nov 11, 2015
Acceptance Date May 12, 2015
Online Publication Date Dec 21, 2015
Publication Date Dec 21, 2015
Deposit Date Dec 13, 2022
Publicly Available Date Dec 14, 2022
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 731-732
Series Title SAI Intelligent Systems Conference (IntelliSys)
Book Title 2015 SAI Intelligent Systems Conference (IntelliSys)
ISBN 978-1-4673-7605-1
DOI https://doi.org/10.1109/IntelliSys.2015.7361221
Keywords Recommender systems, Social network services, Intelligent systems, Computational intelligence, Electronic mail, Measurement, Conferences, Recommendation, Influence, Trust, Social network
Public URL https://uwe-repository.worktribe.com/output/10252820
Publisher URL https://ieeexplore.ieee.org/document/7361221
Related Public URLs https://ieeexplore.ieee.org/xpl/conhome/7347192/proceeding

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Copyright Statement
This is the author’s accepted manuscript. The final published version is available here: https://ieeexplore.ieee.org/document/7361221

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