Service composition has risen from the need to make information systems more flexible and open. The Service Oriented Architecture has become the reference architecture model for applications carried by the impetus of Internet (Web). In fact, information systems are able to expose interfaces through the Web which has increased the number of available Web services. On the other hand, with the emergence of the Web 2.0, service composition has evolved toward web users with limited technical skills. Those end-users, named Y generation, are participating, creating, sharing and commenting content through the Web. This evolution in service composition is translated by the reference paradigm of Mashup and Mashup editors such as Yahoo Pipes ! This paradigm has established the service composition within end users community enabling them to meet their own needs, for instance by creating applications that do not exist. Additionally, Web 2.0 has brought also its social dimension, allowing users to interact, either directly through the online social networks or indirectly by sharing, modifying content, or adding metadata.
In this presentation, I will talk about the research work achieved during my thesis in order to support the evolving concept of service composition through meaningful contributions. The main contribution is indeed the introduction of the social dimension within the process of building a composite service through end users’ dedicated environments. In fact, this concept of social dimension considers the activity of compositing services (creating a Mashup) as a social activity. This activity reveals social links between users based on their similarity in selecting and combining services. These links could be an interesting dissemination means of expertise, accumulated by users when compositing services. In other terms, based on frequent composition patterns, and similarity between users, when a user is editing a Mashup, dynamic recommendations are proposed. These recommendations aim to complete the initial part of Mashup already introduced by the user. This concept has been explored through (i) a step-by-step Mashup completion by recommending a single service at each step, and (ii) a full Mashup completion approaches by recommending the whole sequence of services that could complete the Mashup.
Beyond pushing a vision for integrating the social dimension in the service composition process, I will talk about the particular constraint of this interactive recommendation system in terms of response time. In this regard, we have developed robust algorithms adapted to the specificities of our problem. Whereas a composite service is considered as a sequence of basic service, finding similarities between users comes first to find frequent patterns (subsequences) and then represent them in an advantageous data structure for the recommendation algorithm. The proposed algorithm FESMA, provide exactly those requirements based on the FSTREE structure with interesting results compared to the prior art. Finally, I will conclude by discussing the obtained results and how to use them for future work.
