【摘要】 首先分析了挖掘整个大型时态数据库时可能存在的两个问题,提出了解决的一种新方法。该方法采用“先分后合”的思想:先将大型数据库划分成多个小型数据集,接着对这些数据集进行四次裁剪后再进行综合评价,最后挖掘出潜在的Burst模式。实验结果表明,该方法准确有效。挖掘出的Burst模式给公司决策者在制定决策的时候提供参考帮助和支持。更多还原

【Abstract】 How to effectively discover potentially useful knowledge from large databases is an important yet challenging issue. The paper firstly pointed out there would be two problems in mining very large temporal databases with experimental results, and then proposed a new method to solve the two problems. This approach first partitioned a database into several small datasets. And then the Burst patterns were dug up after four times pruning on the data. The experimental results show that the proposed method is accurate and efficient, and the Burst patterns are useful for decision-making in business.更多还原