As we move from a Web of data to a Web of services, enhancing the capabilities of the current Web search engines with effective and efficient techniques for Web services retrieval and selection becomes an important issue. In this dissertation, we present a framework that identifies the top-k Web service compositions according to the user fuzzy preferences based on a fuzzification of the Pareto dominance relationship. We also provide a method to improve the diversity of the top-k compositions. An efficient algorithm is proposed for each method. We evaluate our approach through a set of thorough experiments. After that, we consider the problem of Web service selection under multiple users preferences. We introduce a novel concept called majority service skyline for this problem based on the majority rule. This allows users to make a “democratic” decision on which Web services are the most appropriate. We develop a suitable algorithm for computing the majority service skyline. We conduct a set of thorough experiments to evaluate the effectiveness of the majority service skyline and the efficiency of our algorithm. We then propose the notion of α-dominant service skyline based on a fuzzification of Pareto dominance relationship, which allows the inclusion of Web services with a good compromise between QoS parameters, and the exclusion ofWeb services with a bad compromise between QoS parameters. We develop an efficient algorithm based on R-Tree index structure for computing efficiently the α-dominant service skyline. We evaluate the effectiveness of the α-dominant service skyline and the efficiency of the algorithm through a set of experiments. Finally, we consider the uncertainty of the QoS delivered by Web services. We model each uncertain QoS attribute using a possibility distribution, and we introduce the notion of pos-dominant service skyline and the notion of nec-dominant service skyline that facilitates users to select their desired Web services with the presence of uncertainty in their QoS. We then developappropriate algorithms to efficiently compute both the pos-dominant service skyline and nec-dominant service skyline. We conduct extensive sets of experiments to evaluate the proposed service skyline extensions and algorithms
