Description

With the rapid development of technologies based on Web service, large quantities of Web services are available on the Internet. Web service recommendation aims at helping users in designing and developing service-oriented software systems. How to recommend web services with better QoS value receives a lot of attention. The modern information systems on the Internet are services integrated software components for the support of interoperable machine to machine interaction over a network. Web services have been widely employed for building service-oriented applications in both industry and academia in recent years. The number of publicly available Web services is steadily increasing on the Internet. However, this proliferation makes it hard for a user to select a proper Web service among a large amount of service candidates. A web service is a software system designed to support interoperable machine-to-machine interaction over a network. Web services have been widely employed for building service-oriented applications in both industry and academia in recent years. The number of publicly available Web services is steadily increasing on the Internet. However, this proliferation makes it hard for a user to select a proper Web service among a large amount of service candidates. The existing methods have rarely taken into account the peculiar characteristics of Web service QoS when making QoS predictions. In this project the system proposed a location-aware personalized CF method for Web service recommendation. The system explored several influential factors of Web service QoS and incorporate them into our QoS prediction method. The proposed approach improves the QoS prediction accuracy and computational efficiency significantly, compared to previous CF-based methods.