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http://dx.doi.org/10.5762/KAIS.2011.12.8.3689

An Approximate Query Answering Method using a Knowledge Representation Approach  

Lee, Sun-Young (Department of Computer Education, Chungbuk National University)
Lee, Jong-Yun (Department of Computer Education, Chungbuk National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.12, no.8, 2011 , pp. 3689-3696 More about this Journal
Abstract
In decision support system, knowledge workers require aggregation operations of the large data and are more interested in the trend analysis rather than in the punctual analysis. Therefore, it is necessary to provide fast approximate answers rather than exact answers, and to research approximate query answering techniques. In this paper, we propose a new approximation query answering method which is based on Fuzzy C-means clustering (FCM) method and Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed method using FCM-ANFIS can compute aggregate queries without accessing massive multidimensional data cube by producing the KR model of multidimensional data cube. In our experiments, we show that our method using the KR model outperforms the NMF method.
Keywords
Data cube; Approximate query answering; FCM-ANFIS; Data warehouse;
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