据《electronics》官网显示，浙江财经大学东方学院信息学院杨洁老师的合作论文《Service Discovery Method Based on Knowledge Graph and Word2vec》在2022年第11期发表。该期刊被SCI四区收录。

Mashup是一种集成了多个 Web API 的新型应用。随着混搭应用程序开发的不断发展，所使用的 API质量就显得尤为重要。在互联网技术快速发展的背景下，Web API的数量正在迅速增加。混搭开发人员从大量服务中人工选择合适的 API 是不现实的。在现有方法中，一个混搭会与几个 API 相关，因此会存在数据稀疏性的问题；其次会出现对语义信息过度依赖的问题。为了解决当前服务发现方法中的这些问题，我们提出了一种基于知识图谱（SDKG）的服务发现方法。我们将服务相关信息嵌入到知识图谱中，从而减轻数据稀疏性的影响，挖掘服务之间的深层关系，这样就可以提高服务发现的准确性。实验结果表明，与现有的主流业务发现方法相比，该方法在准确性上具有明显优势。

Acknowledgment：Mashup is a new type of application that integrates multiple Web APIs.  For mashup application development, the quality of the selected APIs is particularly important. However, with the rapid development of Internet technology, the number of Web APIs is increasing rapidly.  It is unrealistic for mashup developers to manually select appropriate APIs from a large number of services. For existing methods, there is a problem of data sparsity, because one mashup is related to a few APIs, and another problem of over-reliance on semantic information. To solve these problems in current service discovery approaches, we propose a service discovery approach based on a knowledge map (SDKG). We embed service-related information into the knowledge graph, alleviating the impact of data sparsity and mining deep relationships between services, which improves the accuracy of service discovery. Experimental results show that our approach has obvious advantages in accuracy compared with the existing mainstream service discovery approaches.