Abstract
With the rapid development of service-oriented computing, an overwhelming number of web services have been published online. Developers can create mashups that combine one or multiple services to meet complex business requirements. To speed up the mashup development process, recommending suitable services for developers is a vital problem. In this paper, we address the data sparsity and cold-start problems faced in service recommendation, and propose a novel multi-relational graph convolutional network framework (MRGCN) for service recommendation. Specifically, we first construct a multi-relational mashup-service graph with three types of relations, namely composition relation, functional relation, and tagging relation. These three relations are indispensable and complement each other for capturing multi-view information. Then, the three relations in the graph are seamlessly fused with various strategies. Next, graph convolution is performed on the fused multi-relational graph to capture the high-order relational information between mashups and services. Finally, the relevance between mashup requirements and services is predicted based on the learned features on the graph. We conduct extensive experiments on the ProgrammableWeb dataset and demonstrate that our proposed method can outperform state-of-the-art methods in recommending services when only mashup requirements are available.
Highlights
Service-oriented computing (SOC) has become a significant paradigm for developing low-cost and reliable software applications in software engineering and cloud computing [1]
We conduct a series of experiments on real-world services from ProgrammableWeb, and the results demonstrate the effectiveness of our proposed approach; The rest of this article is organized as follows: Section 2 presents the related work of service recommendation
The reason could be that CMF implicitly considers the semantic relations between mashups and services through the shared topics, while only the semantic similarities between mashups are considered in collaborative filtering (CF)
Summary
Service-oriented computing (SOC) has become a significant paradigm for developing low-cost and reliable software applications in software engineering and cloud computing [1]. Web services are the basic build blocks of service-oriented computing, which encapsulate application functionalities and can be accessed through standard interfaces [2]. An increasing number of web services, mainly in the form of RESTful Web APIs, have been published online. The functionality of an individual service is limited and cannot satisfy the complex requirements of developers. A developer may create a new mashup that can display ratings and reviews of restaurants on a region map by integrating Google Map service and Yelp Service. Creating a mashup can be difficult and time-consuming for the inexperienced developer due to the overwhelming number of services on the Internet. It is vital to proactively recommend appropriate services that can satisfy the developer’s complex requirements and ease the selection burden
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
