A general evaluation measure for document organization tasks

Enrique Amigó, Julio Gonzalo, M. Verdejo
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引用次数: 117

Abstract

A number of key Information Access tasks -- Document Retrieval, Clustering, Filtering, and their combinations -- can be seen as instances of a generic {\em document organization} problem that establishes priority and relatedness relationships between documents (in other words, a problem of forming and ranking clusters). As far as we know, no analysis has been made yet on the evaluation of these tasks from a global perspective. In this paper we propose two complementary evaluation measures -- Reliability and Sensitivity -- for the generic Document Organization task which are derived from a proposed set of formal constraints (properties that any suitable measure must satisfy). In addition to be the first measures that can be applied to any mixture of ranking, clustering and filtering tasks, Reliability and Sensitivity satisfy more formal constraints than previously existing evaluation metrics for each of the subsumed tasks. Besides their formal properties, its most salient feature from an empirical point of view is their strictness: a high score according to the harmonic mean of Reliability and Sensitivity ensures a high score with any of the most popular evaluation metrics in all the Document Retrieval, Clustering and Filtering datasets used in our experiments.
文件组织任务的一般评价方法
许多关键的信息访问任务——文档检索、聚类、过滤以及它们的组合——可以看作是通用的{\em文档组织}问题的实例,该问题在文档之间建立优先级和相关性关系(换句话说,是形成和排列聚类的问题)。据我们所知,尚未对从全球角度评价这些任务进行分析。在本文中,我们为通用文档组织任务提出了两个互补的评估指标——可靠性和灵敏度,这两个指标来自于一组提出的形式约束(任何合适的度量必须满足的属性)。除了是第一个可以应用于任何排序、聚类和过滤任务的混合度量之外,可靠性和灵敏度比以前存在的每个包含任务的评估度量满足更多的正式约束。除了它们的形式属性外,从经验的角度来看,其最显著的特征是它们的严谨性:根据可靠性和灵敏度的调和平均值获得高分,确保在我们实验中使用的所有文档检索,聚类和过滤数据集中使用任何最流行的评估指标获得高分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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