Using Fuzzy FP-tree Model to Discover Associations Among Melancholiac Patient’s Daily Text Messages

• Main Authors: Hong-Wen Chiu, 邱鴻文
• Other Authors: 黃有評
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/ua42em

碩士 === 國立臺北科技大學 === 電機工程系研究所 === 98 === With the constant stress from work load and daily life such as economic and family problems people may show symptoms of melancholia. Even worse, it may eventually turn into depression. However, most people are reluctant to describe it or may not know that they already have it. To help these patients maintain communication normally with other persons, the patients’ daily life text messages are recorded for further analysis. The analytical results would be useful for patients to improve their own social relationship and to reduce the unfortunate occurrence of poor emotional possibilities. In this study a novel system is proposed to analyze patients’ emotion using word segmentation system and fuzzy association rules. The word segmentation system is provided by Academia Sinica, Taiwan for users to input text messages. Critical keywords are selected by the proposed weighted keyword strategy. A fuzzy association model is used to discover frequent keywords mentioned in the speech files and to find out the relation among them. Based on these extracted associations the proposed system can help figure out what the problems a patient has faced. Then, the doctors can give patients some psychological counseling and advice based on these results. Finally, this study presents the analytical results to patients at a fixed interval. The patients’ emotional tables are produced to observe their long-term variations in emotion and to predict any possible emotion reactions in the future.