Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator

Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator

Neil Davis (The University of Sheffield, UK), George Demetriou (The University of Sheffield, UK), Robert Gaizauskas (The University of Sheffield, UK), Yikun Guo (The University of Sheffield, UK) and Ian Roberts (The University of Sheffield, UK)
Copyright: © 2006 |Pages: 18
DOI: 10.4018/jwsr.2006100105
OnDemand PDF Download:
$37.50

Abstract

Text mining technology can be used to assist in finding relevant or novel information in large volumes of unstructured data, such as that which is increasingly available in the electronic scientific literature. However, publishers are not text mining specialists, nor typically are the end user scientists who consume their products. This situation suggests a web services based solution, where text mining specialists process the literature obtained from publishers and make their results available to remote consumers (research scientists). In this paper we discuss the integration of web services and text mining within the domain of scientific publishing and explore the strengths and weaknesses of three generic architectural designs for delivering text mining web services. We argue for the superiority of one of these and demonstrate its viability by reference to an application designed to provide access to the results of text mining over the PubMed database of scientific abstracts.

Complete Article List

Search this Journal:
Reset
Open Access Articles
Volume 14: 4 Issues (2017)
Volume 13: 4 Issues (2016)
Volume 12: 4 Issues (2015)
Volume 11: 4 Issues (2014)
Volume 10: 4 Issues (2013)
Volume 9: 4 Issues (2012)
Volume 8: 4 Issues (2011)
Volume 7: 4 Issues (2010)
Volume 6: 4 Issues (2009)
Volume 5: 4 Issues (2008)
Volume 4: 4 Issues (2007)
Volume 3: 4 Issues (2006)
Volume 2: 4 Issues (2005)
Volume 1: 4 Issues (2004)
View Complete Journal Contents Listing