用英文润色一下下面一段论文:y.After each round of interaction, the consumer estimates the utility of the predicate used in the query, which is useful for planning the next round of interaction. The utility of a predicate 푃 expresses the anticipated accuracy improvement that R푃 brings to M. We define a measure that we call novelty to quantify predicate utility. The basic idea of this measure is to quantify the difference between the data acquired in the interaction to those that the consumer currently possesses. The higher the difference, the more information this interaction brings to the consumer. Let RM:푃 be the records the consumer currently possesses satisfying 푃. The novelty of predicate 푃, denoted as 푈푃 , is defined on RM:푃 and R푃 . More specifically, we consider a binary classification problem that treats RM:푃 and R푃 as samples from class 0 and class 1 respectively, and train a classifier CLF to distinguish between the two sets of records. The utility of 푃 is computed as follows:
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请用中文润色:每一轮交互后,消费者估计查询中使用的谓词的效用,这对规划下一轮交互很有用。谓词 푃 的效用表示 R푃 给 M 带来的预期精确度提高。我们定义了一个称为新颖性的度量来量化谓词效用。这个度量的基本思想是量化交互中获得的数据与消费者当前拥有的数据的差异。差异越大,这次交互为消费者带来的信息就越多。设 RM:푃 为消费者当前拥有满足 푃 的记录。谓词 푃 的新颖性,符号为 푈푃 ,是基于 RM:푃 和 R푃 定义的。更具体地,我们考虑一个二分类问题,将 RM:푃 和 R푃 分别作为类 0 和类 1 的样本,并训练分类器 CLF 来区分这两组记录。计算 푃 的效用如下:
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