Abstract
Model composition is an important problem in model management. In this paper, we propose a new method to support model composition in multi-dimensional data spaces. We define a model as a 6-tuple with input interface and output interface. An algorithm for model composition and execution is given. Moreover, the method has been applied into a practical project. The running statistics showed that there had been 105 instances of model composition, and 89 decision problems had been effectively solved.
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Yu, H., Sun, J., Wu, X., Li, Z. (2007). Model Composition in Multi-dimensional Data Spaces. In: Yao, J., Lingras, P., Wu, WZ., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds) Rough Sets and Knowledge Technology. RSKT 2007. Lecture Notes in Computer Science(), vol 4481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72458-2_55
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DOI: https://doi.org/10.1007/978-3-540-72458-2_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72457-5
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