An Improved Database Classification Algorithm for Multi-database Mining

Authors:
Hong Li;Xuegang Hu;Yanming Zhang
Affiliations:
Department of Computer Science and Technology, Hefei University, China 230001 and Hefei University Key Laboratory of Network and Intelligent Information Processing,;School of Computer & Information, Hefei University of technology, China 230001;Department of Computer Science and Technology, Hefei University, China 230001 and Hefei University Key Laboratory of Network and Intelligent Information Processing,
Venue:
FAW '09 Proceedings of the 3d International Workshop on Frontiers in Algorithmics
Year:
2009

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Abstract

Database classification is a data preprocessing technique for multi-database mining. To reduce search costs in the data from all databases, we need to identify those databases which are most likely relevant to a data mining application. Based on the related research, the algorithm GreedyClass and BestClassification [7]are improved in order to optimize the time complexity of algorithm and to obtainthe best classification from m given databases. Theoretical analysis and experimental results show the efficiency of the proposed algorithm.