Efficient QoS-based Service Selection with Consideration of User Requirements

Many QoS-based service selection algorithms are complex and time-consuming, and sometimes require a lot of manual efforts from users. As a result, users' real-time searching experiences may not be good when there are many candidate services, because it could be very slow to calculate the ranking scores of services. In this paper, we want to improve the efficiency of the selection process by using a simple vector space model. We also consider the actual QoS requirements from users in the ranking process, which is missing in many current systems. Our experiment results show a big improvement on the system efficiency without losing much on the accuracy when compared with a well-known algorithm -- skyline computation.