A Duplex Feedback Based Web Service Recommendation Method

Jian Luo, Hai-Yan Wang

(College of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)



Abstract:

In the most current Web Services recommendation methods, rating data from service users is rare and the accuracy of the recommendation results cannot be effectively guaranteed. To address this problem, this paper firstly presents a new web service recommendation framework. Based on the proposed framework, a duplex feedback based web service recommendation method (DFBWSRM) is then elaborated, which includes both implicit and explicit feedback data for the calculation of similarities of user preferences during the finding, binding and rating of services. A coordinated recommendation algorithm is also listed in detail. The simulation results demonstrate that the proposed method can satisfyingly increase the accuracy of recommendation results and better meet the requirements of service users.

Key words:  feedback  web service  recommendation  quality of service (QoS) endation efficiently and, in this way, improve the service recommendation quality. References

DOI：10.11916/j.issn.1005-9113.2014.06.006

Clc Number:TP393

Fund: