DocumentCode
1670621
Title
An Artificial Neural Network for Predicting Service Rating in the Presence of Rating Manipulation
Author
Ping Zhao ; Xinfeng Ye
Author_Institution
Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand
fYear
2015
Firstpage
608
Lastpage
615
Abstract
Accurately predicting a user´s rating to a service is a challenging task in the presence of malicious users that manipulate the ratings to services. Many existing service rating systems lack the ability that counter the manipulation of rating systems. This paper proposed an artificial neural network (ANN) based service rating scheme that counters the manipulation of service ratings. The scheme takes into account of both similarity-based rating and the ratings given by representative users when predicting a user´s rating to a service. Some experiments were carried out to compare the prediction accuracy of the proposed scheme with a well-known existing scheme WSRec [26]. The results show that the proposed scheme provides more accurate rating predictions in the presence of a large amount of malicious users.
Keywords
Web services; neural nets; recommender systems; Web service; artificial neural network; service rating manipulation; service rating prediction; service recommendation; similarity-based rating; Accuracy; Artificial neural networks; Collaboration; Filtering; Neurons; Radiation detectors; Training; artificial neural network; service recommendation;
fLanguage
English
Publisher
ieee
Conference_Titel
Services Computing (SCC), 2015 IEEE International Conference on
Conference_Location
New York, NY
Print_ISBN
978-1-4673-7280-0
Type
conf
DOI
10.1109/SCC.2015.88
Filename
7207406
Link To Document