Xuanzhe Liu, Qi Zhao, Gang Huang, Hong Mei, Teng Teng
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Composing Data-Driven Service Mashups with Tag-Based Semantic Annotations
Spurred by Web 2.0 paradigm, there emerge large numbers of service mashups by composing readily accessible data and services. Mashups usually address solving situational problems and require quick and iterative development lifecyle. In this paper, we propose an approach to composing data driven mashups, based on tag-based semantics. The core principle is deriving semantic annotations from popular tags, and associating them with programmatic inputs and outputs data. Tag-based semantics promise a quick and simple comprehension of data capabilities. Mashup developers including end-users can intuitively search desired services with tags, and combine several services by means of data flows. Our approach takes a planning technique to retrieving the potentially relevant composition opportunities. With our graphical composition user interfaces, developers can iteratively modify, adjust and refine their mashups to be more satisfying.