An Efficient Knowledge-Graph-Based Web Service Recommendation Algorithm

An Efficient Knowledge-Graph-Based Web Service Recommendation Algorithm
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一种高效的基于知识图谱的Web服务推荐算法

DOI:
10.3390/sym11030392
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发表时间:
2019-03
期刊:
影响因子:
2.7
通讯作者:
Zhang Xiuguo
Zhang Xiuguo
中科院分区:
综合性期刊4区
文献类型:
--
作者:
Cao Zhiying;Qiao Xinghao;Jiang Shuo;Zhang Xiuguo

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使用语义信息可以帮助从各种可用的(不同语义的)服务中准确地找到合适的服务,并且可以在Web服务知识图中详细描述Web服务的语义信息。提出了一种基于知识图表示学习(kg-WSR)的Web服务推荐算法。该算法将知识图的实体和关系嵌入到低维向量空间中。通过计算低维空间中服务实体之间的距离,将协同过滤算法推荐方法中未考虑的服务关系信息纳入推荐算法中,提高推荐结果的准确性。实验结果表明,该算法不仅能有效提高推荐的准确率、召回率和覆盖率,而且在一定程度上解决了冷启动问题。
Using semantic information can help to accurately find suitable services from a variety of available (different semantics) services, and the semantic information of Web services can be described in detail in a Web service knowledge graph. In this paper, a Web service recommendation algorithm based on knowledge graph representation learning (kg-WSR) is proposed. The algorithm embeds the entities and relationships of the knowledge graph into the low-dimensional vector space. By calculating the distance between service entities in low-dimensional space, the relationship information of services which is not considered in recommendation approaches using a collaborative filtering algorithm is incorporated into the recommendation algorithm to enhance the accurateness of the result. The experimental results show that this algorithm can not only effectively improve the accuracy rate, recall rate, and coverage rate of recommendation but also solve the cold start problem to some extent.
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