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An authorization policy management framework for dynamic medical data sharing

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conference contribution
posted on 2007-01-01, 00:00 authored by F Al-Neyadi, Jemal AbawajyJemal Abawajy
In this paper, we propose a novel feature reduction approach to group words hierarchically into clusters which can then be used as new features for document classification. Initially, each word constitutes a cluster. We calculate the mutual confidence between any two different words. The pair of clusters containing the two words with the highest mutual confidence are combined into a new cluster. This process of merging is iterated until all the mutual confidences between the un-processed pair of words are smaller than a predefined threshold or only one cluster exists. In this way, a hierarchy of word clusters is obtained. The user can decide the clusters, from a certain level, to be used as new features for document classification. Experimental results have shown that our method can perform better than other methods.

History

Pagination

313 - 318

Location

Jeju Island, Korea

Open access

  • Yes

Start date

2007-10-11

End date

2007-10-13

ISBN-13

9780769530062

ISBN-10

0769530060

Language

eng

Notes

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Publication classification

E1 Full written paper - refereed

Copyright notice

2007, IEEE

Title of proceedings

IPC 2007 proceedings : the 2007 International Conference on Intelligent Pervasive Computing