In view of the fact that the QoS-based service selection method in the current service selection method is less concerned with the personality attribute characteristics of the service requesters and the service selection method based on collaborative filtering, the service providers', Based on the characteristics of the personality of the service requester, this paper describes the user correlation by defining the similarity and domain relevance of the user, and the calculation method of the recommended credibility is given by using the credible measurement theory. Using the analytic hierarchy process (AHP) to determine the weight of each correlation factor, this paper proposes a credible service selection model based on collaborative filtering service selection trust model (SSTM). The simulation results show that the model can effectively improve the efficiency of service selection and resist the attack of malicious feedback. There are two major innovations as following: Firstly, to make a introduction of user relevance to reflect the degree of close between two users (service requester) under the network environment; to apply the user’s personality attribute characteristics to the service provider reputation value during the prediction, to improve the accuracy of service selection by reducing the size of service providers. Secondly, combining user relevance and recommendation credibility organically, using AHP to determine the weight of relevant factors in the service selection index system so that we can make the reputation of the predicted service provider more reliable and effectively resist the malicious user feedback.
[1]
Douglas B. Terry,et al.
Using collaborative filtering to weave an information tapestry
,
1992,
CACM.
[2]
Gang Yin,et al.
Research on network-based large-scale collaborative development and evolution of trustworthy software
,
2014
.
[3]
Shao Kun,et al.
Normal Distribution Based Dynamical Recommendation Trust Model
,
2012
.
[4]
Meng Li,et al.
CoWS: An Internet-Enriched and Quality-Aware Web Services Search Engine
,
2011,
2011 IEEE International Conference on Web Services.
[5]
Hong Guo,et al.
Dynamic trust calculation model and credit management mech-anism of online trading
,
2014
.
[6]
Chen Xin.
Research on Grid Resource Scheduling Algorithm
,
2009
.
[7]
Ding Ya.
Trusted Cloud Service
,
2015
.
[8]
Hao Chen,et al.
A light-weight, secure and trusted virtual execution environment
,
2012
.
[9]
Qian Tao,et al.
A novel prediction approach for trustworthy QoS of web services
,
2012,
Expert Syst. Appl..