We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Semantically enabled data mashups using ontology learning method for Web APIs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yong-Ju Lee ; Sch. of Comput. Inf., Kyungpook Nat. Univ., Sangju, South Korea ; Jeong-Hong Kim

Data mashups enable users to create new applications by combining Web APIs from several data sources. However, the existing data mashup framework requires some programming knowledge, hence it is not suitable for use by non-expert users. In this paper, we present an ontology learning method that builds semantic ontologies automatically, and propose an interactive composition approach based on a similarity search method that supports the dynamic composition of APIs. These techniques allow mashup developers to automate the discovery and composition of Web APIs eliminating the need for programmer involvement.

Published in:

Computing, Communications and Applications Conference (ComComAp), 2012

Date of Conference:

11-13 Jan. 2012