A case-based reasoning system with the two-dimensional reduction technique for leisure constraints classification

• Main Authors: Yu-Cheng Huang, 黃鈺程
• Other Authors: Yan-Kwang Chen
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/3wqgs7

碩士 === 臺中技術學院 === 流通管理系碩士班 === 99 === Purpose－This study aims to develop a case-based reasoning (CBR) system for leisure constraints. This system could infer leisure constraints the visitors perceive according to their demographic variables, and thus could offer marketing strategies of leisure constraints negotiation. Design/methodology/approach－The cases for building the CBR system were collected based on the survey of people who visited the Yamay Discovery World. Each case consists of features(demographic variables) and perceived constraints. Then, a cluster analysis was made to classify the cases into mutually different sets using perceived constraints. Finally, the CBR system was built up with the application of genetic algorithms(GAs) to feature and case reductions. Findings－The cases are divided mutually into four sets, namely no constraints(NC), intrapersonal constraints(IC), strong constraints(SC) and external constraints(EC). According to reduced features (demographic variables) the system can efficiently infer the set a new case (visitor) belongs. Originality/value－This study pioneers on applications of artificial intelligence(AI) techniques to inferring perceived constraints of visitors, which is usually not easy to catch on.