A framework for discovering and classifying ubiquitous services in digital health ecosystems

Publisher:
Academic Press Inc Elsevier Science
Publication Type:
Journal Article
Citation:
Journal of Computer and System Sciences, 2011, 77 (4), pp. 687 - 704
Issue Date:
2011-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2011000692OK.pdf1.19 MB
Adobe PDF
A digital ecosystem is a widespread type of ubiquitous computing environment comprised of ubiquitous, geographically dispersed, and heterogeneous species, technologies and services. As a subdomain of the digital ecosystems, digital health ecosystems are crucial for the stability and sustainable development of the digital ecosystems. However, since the service information in the digital health ecosystems exhibits the same features as those in the digital ecosystems, it is difficult for a service consumer to precisely and quickly retrieve a service provider for a given health service request. Consequently, it is a matter of urgency that a technology is developed to discover and classify the health service information obtained from the digital health ecosystems. A survey of state-of-the-art semantic service discovery technologies reveals that no significant research effort has been made in this area. Hence, in this paper, we present a framework for discovering and classifying the vast amount of service information present in the digital health ecosystems. The framework incorporates the technology of semantic focused crawler and social classification. A series of experiments are conducted in order to respectively evaluate the framework and the employed mathematical model.
Please use this identifier to cite or link to this item: