Abstract
Data warehouse plays an inevitable role for decision making in any organization. Therefore, high quality of data warehouse must be maintained using appropriate models, techniques and tools. Researchers and experimenters in past, have proposed various structural metrics to compute the understandability of data warehouse conceptual model. The main focus of our research work in this paper, is to generate heuristic rules using data mining classification algorithms and validate them using fuzzy logic technique to predict the understandability of data warehouse conceptual model. The results are compared with previously conducted controlled experiments to prove and validate the effectiveness of fuzzy prediction system.
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Singh, A., Garg, J., Rastogi, A., Dahiya, N. (2020). Analyzing the Understandability of Data Warehouse Conceptual Model Using Fuzzy Logic Techniques. In: Kumar, A., Paprzycki, M., Gunjan, V. (eds) ICDSMLA 2019. Lecture Notes in Electrical Engineering, vol 601. Springer, Singapore. https://doi.org/10.1007/978-981-15-1420-3_104
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DOI: https://doi.org/10.1007/978-981-15-1420-3_104
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