(untitled) (International Journal of Engineering and Computer Science, 2016)
The increase in the numbers of web services with similar functionalities, leads to the increase in the number of users which are dependent on web service recommendation systems. Currently, the service users pay more importance to non-functional properties also known as ‘Quality of Service(QoS)’ along with finding and going for pertinent web services. The Collaborative filtering method helps in predicting the QoS values of the web services efficiently. The current recommendation systems seldom take into account the personalized effect of the users and pertinent services in determining the synonymy among the users and services. The prospective system is based on ranking oriented hybrid methods assimilating user-based and item-based QoS augury. Quite a few non-functional properties depend on the user and the associated service location. Therefore, the system puts to use the location information of the users and services while choosing synonymous neighbors for the target user and service, consequently making personalized service recommendation for service users. The technique is used persistently for improving the QoS over the internet in the current scenario where quality of the content delivered is of utmost importance for an ideal scope of service improvement and enhancement.