Contextualized Behavior Mining for Event Prediction in Telematics

• Main Authors: Yi-Cheng Hsieh, 謝宜錚
• Other Authors: Soe-Tsyr Yuan
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/45110631750724545484

碩士 === 輔仁大學 === 資訊管理學系 === 91 === Taking into account the three aspects (person, location, and time), this research analyzes, learns, and predicts a customer’s contextualized behavior, timely furnishing the customer with the important contextualized information in prevention of mishap. The current problem domain this research works on is for the auto insurance industry. The combination of data mining and mobile location-based services is applied to the auto insurance industry in an attempt of providing auto customers with personalized contextualized services. This not only retains old customers but also attracts new customers to achieve the goal of M-CRM for the auto insurance industry. For instance, insurance brokers can provide three types of precautious information (that is personalized and contextualized) regarding steal, scrape, and emergency for customers passing through certain locations at certain time.