Chapter

Rough Sets and Knowledge Technology

Volume 4481 of the series Lecture Notes in Computer Science pp 443-450

Model Composition in Multi-dimensional Data Spaces

  • Haihong YuAffiliated withCollege of Computer Science and Technology, Jilin University, 130012 ChangchunKey Laboratory of Symbolic Computation and Knowledge Engineering, of Ministry of Education, 130012 Changchun
  • , Jigui SunAffiliated withCollege of Computer Science and Technology, Jilin University, 130012 ChangchunKey Laboratory of Symbolic Computation and Knowledge Engineering, of Ministry of Education, 130012 Changchun
  • , Xia WuAffiliated withCollege of Computer Science and Technology, Jilin University, 130012 ChangchunKey Laboratory of Symbolic Computation and Knowledge Engineering, of Ministry of Education, 130012 Changchun
  • , Zehai LiAffiliated withCollege of Computer Science and Technology, Jilin University, 130012 ChangchunKey Laboratory of Symbolic Computation and Knowledge Engineering, of Ministry of Education, 130012 Changchun

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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.

Keywords

Decision Support System Model Management Model Composition Multi-dimension Data