Abstract: There are more and more e-Learning services used in computer supported collaborative learning, hence it is becoming important to locate proper e-Learning services in an accurate and efficient way. In the design of this paper, an annexed algorithm named eLSDAUS is proposed to improve the existing semantic-based e-Learning service matchmaking algorithm. In the algorithm, a new factor—user satisfaction which is the users feeling about the result of service discovery is led-in. This algorithm allows users to take part in the process of e-Learning service discovery, and also allows them evaluate the result of service discovery. Users evaluation in the form of user satisfaction is fed back to the system. Adopting an amendatory function which takes the user satisfaction as input, the system modifies the weights of each property of the advertise service, and then the total match degree of service discovery up to the best. 2 methods are adopted to encourage users to use the e-Learning service discovery system. Experiments indicate that compared with the traditional algorithms, the precision of the service discovery is improved more than 3 percent as the number of advertisement services is up to 10000, and with the increase of advertisement services sum, the effect will be better. After learning for 127 days, over 93% students are satisfied with the e-Learning service discovery result.