Home // WEB 2013, The First International Conference on Building and Exploring Web Based Environments // View article

Algorithm for Automatic Web API Composition

Authors:
Yong-Ju Lee

Keywords: automatic composition algorithm; semantic data mashup; ontology learning method; Web API

Abstract:
Data mashup is a special class of mashup application that combines Web APIs from several data sources to generate a new and more valuable dataset. Although the data mashup has become very popular over the last few years, there are several challenging issues when combining a large number of APIs into the data mashup, especially when composite APIs are manually integrated by mashup developers. This paper proposes a novel algorithm for automatic composition of Web APIs. The proposed algorithm consists of constructing a direc-ted similarity graph and searching composition candidates from the graph. We construct a directed similarity graph which presents the semantic functional dependency between the inputs and the outputs of Web APIs. We generate directed acyclic graphs (DAGs) that can produce the output satisfying the desired goal. We rapidly prune APIs that are guaranteed not to involve the composition in order to produce the DAGs efficiently. The algorithm is evaluated using a collection of RE-ST and SOAP APIs extracted from ProgrammableWeb.

Pages: 57 to 62

Copyright: Copyright (c) IARIA, 2013

Publication date: January 27, 2013

Published in: conference

ISSN: 2308-4421

ISBN: 978-1-61208-248-6

Location: Seville, Spain

Dates: from January 27, 2013 to February 1, 2013