Yang, H. orcid.org/0000-0002-3372-4801, Zhang, M. and Shi, Z. (2004) Association-rule Based Information Resource Selection. In: Zhang, C., Guesgen, H.W. and Yeap, W-K., (eds.) PRICAI 2004: Trends in Artificial Intelligence. The 8th Pacific Rim International Conference on Artificial Intelligence, August 9-13, 2004, Auckland, New Zealand. Lecture Notes in Computer Science, 3157 . Springer, Berlin, Heidelberg , pp. 9-13.
Abstract
The proliferation of information sources available on the Wide World Web has resulted in a need for database selection tools to locate the potential useful information sources with respect to the user’s information need. Current database selection tools always treat each database independently, ignoring the implicit, useful associations between distributed databases. To overcome this shortcoming, in this paper, we introduce a data-mining approach to assist the process of database selection by extracting potential interesting association rules between web databases from a collection of previous selection results. With a topic hierarchy, we exploit intraclass and interclass associations between distributed databases, and use the discovered knowledge on distributed databases to refine the original selection results. We present experimental results to demonstrate that this technique is useful in improving the effectiveness of database selection.
Metadata
Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer-Verlag Berlin Heidelberg 2004. This is an author produced version of a paper subsequently published in LNCS. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 17 May 2017 15:49 |
Last Modified: | 24 Mar 2018 18:05 |
Published Version: | https://doi.org/10.1007/978-3-540-28633-2_60 |
Status: | Published |
Publisher: | Springer, Berlin, Heidelberg |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | https://doi.org/10.1007/978-3-540-28633-2_60 |