Yang, H. orcid.org/0000-0002-3372-4801 and Zhang, M. J. (2004) Hierarchical Classification for Multiple, Distributed Web Databases. International Journal of Computer and Their Applications, 11 (2). pp. 118-130. ISSN 1076-5204
Abstract
The proliferation of online information resources increases the importance of effective and efficient distributed searching. Our research aims to provide an alternative hierarchical categorization and search capability based on a Bayesian network learning algorithm. Our proposed approach, which is grounded on automatic textual analysis of subject content of online web databases, attempts to address the database selection problem by first classifying web databases into a hierarchy of topic categories. The experimental results reported demonstrate that such a classification approach not only effectively reduces the class search space, but also helps to significantly improve the accuracy of classification performance.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 ISCA |
Keywords: | Hierarchical classification; Bayesian classifiers; multiple web databases |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 28 Mar 2017 13:37 |
Last Modified: | 28 Mar 2017 13:37 |
Status: | Published |
Publisher: | ISCA: International Society for Computers and Their Applications |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:110475 |