Summary in Action: A Trade-off between Effectiveness and Efficiency in Multidimensional Relevance Estimation

被引:1
|
作者
Banerjee, Somnath [1 ]
Upadhyay, Rishabh [2 ]
Pasi, Gabriella [2 ]
Viviani, Marco [2 ]
机构
[1] Univ Tartu, Inst Comp Sci, Tartu, Estonia
[2] Univ Milano Bicocca, Dept Informat Syst & Commun, Milan, Italy
基金
欧盟地平线“2020”;
关键词
Information Retrieval; Multidimensional Relevance; Correctness; Credibility; Effectiveness-Efficiency;
D O I
10.1109/WI-IAT59888.2023.00022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In domain-specific search, effectiveness depends on considering multiple dimensions of relevance, beyond topicality, related to the domain involved. Estimating additional relevance dimensions can affect efficiency because the computation of relevance scores is time-consuming if performed on the full document, especially for query-dependent dimensions. Hence, this article introduces an approach for improving effectiveness in domain-specific search by considering multiple dimensions of relevance, namely topicality, correctness, and credibility. To address efficiency, we propose a re-ranking approach that estimates domain-specific relevance scores on document summaries, rather than full documents. We validate the proposed solution by performing the AdHoc Retrieval task from the TREC 2020 Health Misinformation Track, a domain that crucially relies on the considered relevance dimensions. Our findings underscore the potential of our approach with respect to both effectiveness and efficiency.
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页码:119 / 126
页数:8
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