文章基本信息

标题：Recommending Optimal API Orchestration with Mining Frequent Mashup Patterns
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作者：Dunlu Peng ; Lei Xie ; Duan Kai 等
期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2014
卷号：7
期号：3
页码：233-250
DOI：10.14257/ijgdc.2014.7.3.24
出版社：SERSC
摘要：As more and more organizations publish their data or services through Open APIs on the Internet, mashup applications have captured a lot of attention in recent years. However, as the number and categories of Open APIs grow rapidly, efficiently creating optimal mashup applications becomes a crucial issue for making the technology of mashup more applicable. In this work, we present a Mashup Directed Orchestration Model (MDOM) to depict the mashup patterns with a graph-based model on the basis of mashup orientation. According to the features of MDOM, by taking advantage of the theory of directed graph and the strategies used in the algorithms for discovering frequent sub-graphs, an algorithm named as FSOMM is presented to efficiently mine the frequent orchestration patterns hidden in the MDOMs. These discovered frequent orchestration patterns provide us a promising way to create optimal mashup applications. In addition, the performance of the proposed approach is verified by implementing a series of experiments on both synthetic and real datasets.
关键词：Mahsup application; API orchestration; Frequent mashup pattern; Web data ; integration