• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.551-557
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• 2015

Synchronization methods for shared data need to be selected properly based on characteristics of data and applications. In this paper we suggest a new semantic synchronization method, semanticAppr, for non_transactional data in disconnected mode. Our approach reduces loss of works in cooperative environments by weakening constraint of serializability. In addition it reduces data transfer by sending operation log instead document itself.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.60-64
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• 2010

To discover association rules from nontransactional data, there have been many studies on discretization of attribute values. These studies do not reflect the change of discovered rules' confidence according to the change of the ranges of the discretized attributes, and perform the discretization stage and the rule discovery stage independently. This causes the ranges of attributes not properly discretized, thereby making the rules having high confidence excluded in the result set. To solve this problem, we propose a novel method that performs the discretization and rule discovery stages simultaneously in order to discretize ranges of attributes in such a way that the rules having high confidence are discovered well. To the end, we perform hierarchical clustering on the attributes in the right hand side of rules, then do characterization on every cluster thus obtained. The experimental result demonstrates that our method discovers the rules having high confidence better than existing methods.