Information retrieval (IR) evaluation measures are cornerstones for determining the suitability and task performance efficiency of retrieval systems. Their metric and scale properties enable to compare one system against another to establish differences or similarities. Based on the representational theory of measurement, this paper determines these properties by exploiting the information contained in a retrieval measure itself. It establishes the intrinsic framework of a retrieval measure, which is the common scenario when the domain set is not explicitly specified. A method to determine the metric and scale properties of any retrieval measure is provided, requiring knowledge of only some of its attained values. The method establishes three main categories of retrieval measures according to their intrinsic properties. Some common user-oriented and system-oriented evaluation measures are classified according to the presented taxonomy.
翻译:摘要:信息检索(IR)评估指标是确定检索系统适用性和任务性能效率的基石。它们的度量和比例属性可以让我们比较一个系统与另一个系统,从而确定差异或相似性。基于测量的表征理论,本文通过利用检索指标本身含有的信息,确定了这些属性。本文建立了检索指标的内在框架,即当域集没有明确指定时,检索指标的公共情形。提供了一种方法来确定任何检索指标的度量和比例属性,只需要知道它的一些达到值。该方法将检索指标根据其内在属性分为三个主要类别, 并根据提供的分类方法,将一些常见的面向用户和面向系统的评估指标进行了分类。