Deakin University
abawajy-authorizationpolicy-2007.pdf (271.05 kB)

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.



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Jeju Island, Korea

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Publication classification

E1 Full written paper - refereed

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2007, IEEE

Title of proceedings

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