A normal-distribution based reputation model

Abdel-Hafez, Ahmad, Xu, Yue, & Josang, Audun (2014) A normal-distribution based reputation model. Lecture Notes in Computer Science : Trust, Privacy, and Security in Digital Business, 8647(2014), pp. 144-155.

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Rating systems are used by many websites, which allow customers to rate available items according to their own experience. Subsequently, reputation models are used to aggregate available ratings in order to generate reputation scores for items. A problem with current reputation models is that they provide solutions to enhance accuracy of sparse datasets not thinking of their models performance over dense datasets. In this paper, we propose a novel reputation model to generate more accurate reputation scores for items using any dataset; whether it is dense or sparse. Our proposed model is described as a weighted average method, where the weights are generated using the normal distribution. Experiments show promising results for the proposed model over state-of-the-art ones on sparse and dense datasets.

Impact and interest:

4 citations in Scopus
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21 since deposited on 29 Sep 2014
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ID Code: 76394
Item Type: Journal Article
Refereed: Yes
Additional Information: Paper presented in the 11th International Conference, TrustBus 2014, Munich, Germany, September 2-3, 2014.
Additional URLs:
DOI: 10.1007/978-3-319-09770-1_13
ISBN: 9783319097695
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Springer
Deposited On: 29 Sep 2014 22:42
Last Modified: 03 Oct 2015 00:47

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