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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, George Demetriou, Robert Gaizauskas, Yikun Guo, Ian Roberts
Copyright: © 2006 |Volume: 3 |Issue: 4 |Pages: 18
ISSN: 1545-7362|EISSN: 1546-5004|ISSN: 1545-7362|EISBN13: 9781615204557|EISSN: 1546-5004|DOI: 10.4018/jwsr.2006100105
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MLA

Davis, Neil, et al. "Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator." IJWSR vol.3, no.4 2006: pp.95-112. http://doi.org/10.4018/jwsr.2006100105

APA

Davis, N., Demetriou, G., Gaizauskas, R., Guo, Y., & Roberts, I. (2006). Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator. International Journal of Web Services Research (IJWSR), 3(4), 95-112. http://doi.org/10.4018/jwsr.2006100105

Chicago

Davis, Neil, et al. "Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator," International Journal of Web Services Research (IJWSR) 3, no.4: 95-112. http://doi.org/10.4018/jwsr.2006100105

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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.

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