A Novel Approach for API Recommendation in Mashup Development

被引：59

作者：

Li, Chune ^{[1
]}

Zhang, Richong ^{[1
]}

Huai, Jinpeng ^{[1
]}

Sun, Hailong ^{[1
]}

机构：

[1] Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China

来源：

2014 IEEE 21ST INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS 2014) | 2014年

关键词：

mashup development; API recommendation; relational topic model;

D O I：

10.1109/ICWS.2014.50

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Mashing up web services and RESTful APIs is a novel programming approach to develop new applications. As the number of available resources is increasing rapidly, to discover potential services or APIs is getting difficult. Therefore, it is vital to relieve mashup developers of the burden of service discovery. In this paper, we propose a probabilistic model to assist mashup creators by recommending a list of APIs that may be used to compose a required mashup given descriptions of the mashup. Specifically, a relational topic model is exploited to characterize the relationship among mashups, APIs and their links. In addition, we incorporate the popularity of APIs to the model and make predictions on the links between mashups and APIs. Moreover, the statistical analysis on a public mashup platform shows the current status of mashup development and the applicability of this study. Experiments on a large service data set confirm the effectiveness of this proposed approach.

引用

页码：289 / 296

页数：8

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