Automating Mashup Service Recommendation via Semantic and Structural Features. (12th August 2020)

• Record Type: Journal Article
• Authors: Xiong, Wei; Wu, Zhao; Li, Bing; Hang, Bo
• Other Names: Chai Chunlai Guest Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-08-12
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/4960439
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Increasing physical objects connected to the Internet make it possible for smart things to access all kinds of cloud services. Mashup has been an effective way to the rapid IoT (Internet of Things) application development. It remains a big challenge to bridge the semantic gap between user expectations and application functionality with the development of mashup services. This paper proposes a mashup service recommendation approach via merging semantic features from API descriptions and structural features from the mashup-API network. To validate our approach, large-scale experiments are conducted based on a real-world accessible service repository, ProgrammableWeb. The results show the effectiveness of our proposed approach.