文章基本信息

标题：Document level assessment of document retrieval systems in a pairwise system evaluation
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作者：Prabha Rajagopal ; Sri Devi Ravana ; Harshit Srivastava 等
期刊名称：Information Research
印刷版ISSN：1368-1613
出版年度：2017
卷号：22
期号：2
页码：1-11
出版社：University of Sheffield, Department of Information Studies
摘要：The use of averaged topic-level scores can result in the loss of valuable data and can cause misinterpretation of the effectiveness of system performance. This study aims to use the scores of each document to evaluate document retrieval systems in a pairwise system evaluation. The chosen evaluation metrics are document-level precision scores against topic-level average precision (AP) scores, and document-level rank-biased precision (RBP) scores against topic-level RBP at cut-off k (k=100) scores. An analysis of the results of paired significance tests with the use of document-level and topic-level scores are compared to determine the agreement in the obtained numbers of statistically significant information retrieval system pairs. The experiment results at document-level are an effective evaluation unit in the pairwise evaluation of information retrieval systems, with higher numbers of statistically significant (p=0.01) system pairs, compared with the topic-level results and a high percentage of statistically significant agreement with topic-level. This study presents an original viewpoint on measuring the effectiveness of document retrieval systems through pairwise evaluation by using document-level scores as a unit of evaluation in the significance testing instead of the traditional topic-level scores (which involve averaging document scores).
关键词：information retrieval; significance testing; information retrieval evaluation