Abstract
Modelling and understanding various contexts of users is important to enable personalised selection of Web APIs in directories such as Programmable Web. Currently, relationships between users and Web APIs are not clearly understood and utilized by existing selection approaches. In this paper, we present a semantic model of a Web API directory graph that captures relationships such as Web APIs, mashups, developers, and categories. We describe a novel configurable graph-based method for selection of Web APIs with personalised and temporal aspects. The method allows users to get more control over their preferences and recommended Web APIs while they can exploit information about their social links and preferences. We evaluate the method on a real-world dataset from ProgrammableWeb.com, and show that it provides more contextualised results than currently available popularity-based rankings. © 2012 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Dojchinovski, M., Kuchar, J., Vitvar, T., & Zaremba, M. (2012). Personalised graph-based selection of web APIs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7649 LNCS, pp. 34–48). Springer Verlag. https://doi.org/10.1007/978-3-642-35176-1_3
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