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Ontology-Incorporated Mining of Association Rules in Data Warehouse
Abstract
With the rise of the Internet and the development of various electronic information resources, mining useful information from large databases has become one of the most important issues in information research for users. Data warehousing plays a key role in providing data for data mining tools to explore knowledge. However, there are still many problems that cause users to spend extra time to get useful knowledge. In this paper, we explore the problems with contemporary association rule mining in data warehousing systems, explain the essence and propose a framework that incorporates ontologies to resolve the problems. Some interesting research issues and technical challenges on realizing such ontology-incorporated association rule mining in data warehousing systems are pointed out.
Keywords
Data Warehouse; Association Rule Mining; Ontology; Multidimensional Association Rules
Citation Format:
Chin-Ang Wu, Wen-Yang Lin, Ming-Cheng Tseng, Chuan-Chun Wu, "Ontology-Incorporated Mining of Association Rules in Data Warehouse," Journal of Internet Technology, vol. 8, no. 4 , pp. 477-485, Oct. 2007.
Chin-Ang Wu, Wen-Yang Lin, Ming-Cheng Tseng, Chuan-Chun Wu, "Ontology-Incorporated Mining of Association Rules in Data Warehouse," Journal of Internet Technology, vol. 8, no. 4 , pp. 477-485, Oct. 2007.
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Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
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