An approach to discovering multi-temporal patterns and its application to financial databases

作者：Kong Xiaoxiao; Wei Qiang^*; Chen Guoqing

来源：Information Sciences, 2010, 180(6): 873-885.

DOI：10.1016/j.ins.2009.08.026

• Data mining
• Multi-temporal pattern
• Association rule
• Associative financial movement

Managerial decision-making processes often involve data of the time nature and need to understand complex temporal associations among events. Extending classical association rule mining approaches in consideration of time in order to obtain temporal information/knowledge is deemed important for decision support. which is nowadays one of the key Issues in business intelligence. This paper presents the notion of multi-temporal patterns with four different temporal predicates, namely before. during, equal and overlap, and discusses a number of related properties, based on which a mining algorithm is designed This enables Lis to effectively discover multi-temporal patterns in large-scale temporal databases by reducing the database scan in the generation of candidate patterns The proposed approach is then applied to stock markets, aimed at exp

• 出版日期2010-3-15
• 单位清华大学