Modern application development leverages the invocation of a large pool of Web services such as Cloud services and APIs. As the number of Web services keeps growing, it becomes difficult for developers to identify services that can collaborate as part of the same composite application, or that can replace each other in failure cases. Gathering and analyzing Web services social interaction such as composition, substitution, and subscription helps building communities of interoperable services (i.e., likely to collaborate with each other and/or to replace each other). This paper proposes a new approach for recommending interoperable services to developers based on the multi-dimensional analysis of their social interaction history. The approach aims to build communities of services with highly dense interaction relationships. Services part of the same community are recommended to developers as potential collaborators or substitutes. The proposed approach identifies first service leaders. Leaders are particular services with a high interaction rate in the network around which communities are built. Remaining services followers join communities based on their previous interaction experiences. Followers leverage the votes of their experienced neighbors to make their final vote. Experiments on pseudo-real data show that leveraging services social interaction outperforms state-of-the-art approaches.

中文翻译：

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一种推荐可互操作的 Web 服务的社交网络方法

现代应用程序开发利用了大量 Web 服务（例如云服务和 API）的调用。随着 Web 服务数量的不断增长，开发人员很难识别可以作为同一复合应用程序的一部分进行协作或在出现故障时可以相互替换的服务。收集和分析 Web 服务社交交互（例如组合、替换和订阅）有助于构建可互操作的服务社区（即，可能相互协作和/或相互替换）。本文基于对开发者社交互动历史的多维分析，提出了一种向开发者推荐互操作服务的新方法。该方法旨在建立具有高度密集交互关系的服务社区。同一社区的服务部分被推荐给开发者作为潜在的合作者或替代者。提议的方法确定第一服务领导者。领导者是在建立社区的网络中具有高交互率的特殊服务。剩余的服务追随者根据他们以前的互动经验加入社区。追随者利用他们有经验的邻居的投票来进行最后的投票。伪真实数据的实验表明，利用服务社交互动优于最先进的方法。剩余的服务追随者根据他们以前的互动经验加入社区。追随者利用他们有经验的邻居的投票来进行最后的投票。伪真实数据的实验表明，利用服务社交互动优于最先进的方法。剩余的服务追随者根据他们以前的互动经验加入社区。追随者利用他们有经验的邻居的投票来进行最后的投票。伪真实数据的实验表明，利用服务社交互动优于最先进的方法。