Title :
Case Retrieval Strategy Based on GAs and Group Decision-Making Method
Author :
Jiang, Wei ; Yan, Ai-jun ; Wang, Pu
Author_Institution :
Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
Abstract :
Case retrieval is the focal stage in a Case-Based Reasoning (CBR) system. In this paper, a new case retrieval method called CRGCU is proposed in a systematical way, which is based on Genetic Algorithms (GAs) and Group Decision-Making method. First, feature attribute weights of cases are optimized by using GAs. Second, instead of utilizing only one set of feature attribute weights, we calculate similarity based on multiple sets of optimized weights. The result of case retrieval can be obtained at last by adopting Group Cardinal Utility function. The experiments on both static and dynamic data sets illustrate that our method is effective and suitable for CBR system.
Keywords :
case-based reasoning; decision making; genetic algorithms; CRGCU; case based reasoning system; case retrieval strategy; genetic algorithms; group cardinal utility function; group decision making method; Accuracy; Cognition; Databases; Decision making; Gallium; Iris; Training;
Conference_Titel :
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7939-9
Electronic_ISBN :
2156-7379
DOI :
10.1109/ICIECS.2010.5678347