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首页> 外文期刊>Journal of Intelligent Information Systems >Evaluating information retrieval system performance based on user preference
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Evaluating information retrieval system performance based on user preference

机译：根据用户偏好评估信息检索系统的性能

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摘要

One of the challenges of modern information retrieval is to rank the most relevant documents at the top of the large system output. This calls for choosing the proper methods to evaluate the system performance. The traditional performance measures, such as precision and recall, are based on binary relevance judgment and are not appropriate for multi-grade relevance. The main objective of this paper is to propose a framework for system evaluation based on user preference of documents. It is shown that the notion of user preference is general and flexible for formally defining and interpreting multi-grade relevance. We review 12 evaluation methods and compare their similarities and differences. We find that the normalized distance performance measure is a good choice in terms of the sensitivity to document rank order and gives higher credits to systems for their ability to retrieve highly relevant documents.
机译：现代信息检索的挑战之一是将最相关的文档排在大型系统输出的顶部。这要求选择适当的方法来评估系统性能。传统的性能度量（例如精度和召回率）基于二进制相关性判断，不适用于多级相关性。本文的主要目的是提出一个基于用户文档偏好的系统评估框架。结果表明，用户偏好的概念是通用的，可以灵活地正式定义和解释多级相关性。我们回顾了12种评估方法，并比较了它们的异同。我们发现，就对文档等级顺序的敏感性而言，归一化的距离性能度量是一个不错的选择，并且由于系统检索高度相关的文档的能力而给予系统更高的评价。

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