时态空间中时态序列模式的数据挖掘(英文)

Data Mining of Temporal Sequence Patterns in a Temporal Space

时态数据挖掘是目前数据挖掘领域的研究热点。与其它相关研究不同,文章致力于利用时态序列模式挖掘进行预测与决策。首先介绍了时态类型的分类;然后定义了一个新的时态空间模型,用以描述基于不同时态类型、不同属性的各个不同对象的状态,并且为高效地进行预测与决策提供支持;最后,给出了时态空间模型中数据挖掘的四种时态序列模式,对时态数据挖掘的研究具有重要意义。

The temporal data mining has been very important in data mining according to many studies. Our study is motivated by prediction and decision making, which is different from other studies. This paper introduces a class of temporal type. Then, we define a type of new temporal space model describing various states of objects based on the different attributes with the temporal type, which has not been addressed explicitly by previous time model and can provide the prediction and decision in the short time for aforementioned fields. Finally, we give four types of temporal sequence patterns of the data mining in the temporal space model It is very significant to develop the temporal data mining.