Mining the Changes of News Events for Supporting Decision Making

• Main Authors: ChinHui Lai, 賴錦慧
• Other Authors: Duen-Ren Liu
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/53402605011833272145

碩士 === 國立交通大學 === 資訊管理研究所 === 92 === Business environment, in which an enterprise operates locally or globally, has been changing at an unprecedented rate; and business decisions are affected by many uncertain factors from both the inside and outside of the enterprise. Therefore, it is important for an enterprise to track, supervise and manage the existing and forthcoming events pertinent to its business. Recently, many researches have been done on event tracking and detection; however, identifying event changes has not been considered. In this research, we provide a method of combining association rule mining and concept hierarchy for discovering event changes from news events. We focus on specific topics and events to find out trends and changes in news data according to five types of association rules changes, such as emerging pattern, unexpected condition, unexpected consequence, added rule and perished rule. The information of event changes can then be provided to the decision makers for decision support.