An Intrinsic Framework of Information Retrieval Evaluation Measures
April 02, 2023 Β· Declared Dead Β· π Intelligent Systems with Applications
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Authors
Fernando Giner
arXiv ID
2304.00615
Category
cs.IR: Information Retrieval
Citations
1
Venue
Intelligent Systems with Applications
Last Checked
4 months ago
Abstract
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.
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