论文标题
时间关系流的增量信息增益挖掘
Incremental Information Gain Mining Of Temporal Relational Streams
论文作者
论文摘要
本文研究了关系表中信息增益高的数据值的挖掘问题。高信息增益可以帮助数据分析师和二级数据挖掘算法获得有关关键指标之间强大统计依赖性和因果关系的见解。在本文中，我们将研究涉及暂时关系的场景中高信息增益识别的问题，其中不断将新记录添加到关系中。我们表明，可以以增量方式有效地维护信息增益，从而可以监视不断高的信息增益值。
This paper studies the problem of mining for data values with high information gain in relational tables. High information gain can help data analysts and secondary data mining algorithms gain insights into strong statistical dependencies and causality relationship between key metrics. In this paper, we will study the problem of high information gain identification for scenarios involving temporal relations where new records are added continuously to the relations. We show that information gain can be efficiently maintained in an incremental fashion, making it possible to monitor continuously high information gain values.
