Study on the Mining Fuzzy Association Rules on Questionnaire Contains Uncertain Data

• Main Authors: Hsin-Hung Lin, 林欣弘
• Other Authors: Dar-Li Yang
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/dms697

碩士 === 國立虎尾科技大學 === 資訊管理研究所 === 98 === In recent years, data mining has been widely used in various fields. Due to most of information may exist in the hidden knowledge and for promoting better understanding of the events. Data mining therefore is used to mining out the characteristic style of the object data and explains the relationship between the existing behaviors or predicts future results. Today, although there are many rules of relevance information, but most are defined in the information available for the accurate and definitive research. However, this condition is incompatible with the current situation, because people often made various negligence or record defect. This will lead to information obtained is uncertain. Moreover, questionnaires often adopt the numerical sequence answer for convenience, but limiting the thinking of the subjects. This thesis proposes a approach to mining association rules from the uncertain data by combining data mining, fuzzy set and other technology associated with mining methods by extending the study of Weng [18]. The important association rules will no longer are omitted due to the nature of the information by the proposed approach in this research. By computer simulation results showed that the proposed association rules have better and more relational grade in this study. Finally, the Land Rover (Discovery SUV) questionnaire data is used to compare the proposed method in this study by the use of Poly Analyst software. The results showed that the proposed algorithm is superior to the original research results obtained.