Problem:

?? mining relationships in time series data; A new class of relationships in time series data.

traditional methods: discover pair-wise relationships.

Introduction:

Challenge: discovery of complex patterns of relationships between individual time-series. ?? what does this mean?

A common type of relationship in time series data is pairs of time-series with strong Pearson correlations.

In this paper, we define a novel relationship across three time series.

tripole: a group of three time-series, one root node/ two leaf nodes.

Note that a tripole is interesting only if correlation ofT0 withT1+2 is much stronger than correlation of T0 with T1 or T2 individually。

a formal study of tripole and explore their utility in different domains:

需要思考清楚,这个tripole pattern适用于什么domains之下,比如他可以适用于交通数据transportation data/ sea level pressure data 都和区域有关,那如果对于天气,生产,消费的time series关系是否适用,需要认真思考一下。但是我奇怪为什么要衡量T0 and T1+T2的相关性,这种现象在我们的数据中,有什么特殊的代表特征吗。

这种tripole现象,以期并没有进行系统的研究,因此,如何定义tripole,如何发现tripole,如何评估/解释发现的tripole成为了重要的问题。

define; measures to assess its interestingness; discovery with efficiency;

DEFINITIONS:

N time-series, {T1,T2,T3...Tn}

tripole: (T0: T1, T2); root; leaves;

Strength;

Note that while there could be other ways to combine the information in the two leaves, we chose the sum for its simplicity and ease of interpretation.

Jump; 用来判断这个tripole的有趣程度。

PROPOSED APPROACH:

how to discover tripoles in time-series data.

主要描述提出了节约计算的发现tripoles的方法。

EXPERIMENTAL RESULTS AND EVALUATION

两个数据库,海平面压力数据库,location, time series data. 神经影像学数据库,

用到了假设检验,p-value;

PHYSICAL INTERPRETATION OF TRIPOLES

Further validation and study of these tripoles by domain experts could possibly explain the phenomenon that results in the manifestation of these tripoles.

问题:tripole的物理意义应该由该领域的专家进行解释,而且是could possibly explain the phenomenon, 比较弱势的描述。

解释实例:大气中的遥相关,

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