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Improving query and assessment quality in text-based interactive video retrieval evaluation

Conference Paper
Publication Date:
2023
abstract:
Different task interpretations are a highly undesired element in interactive video retrieval evaluations. When a participating team focuses partially on a wrong goal, the evaluation results might become partially misleading. In this paper, we propose a process for refining known-item and open-set type queries, and preparing the assessors that judge the correctness of submissions to open-set queries. Our findings from recent years reveal that a proper methodology can lead to objective query quality improvements and subjective participant satisfaction with query clarity.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Video retrieval
List of contributors:
Coccomini, DAVIDE ALESSANDRO; Messina, Nicola
Handle:
https://iris.cnr.it/handle/20.500.14243/459848
Book title:
ICMR '23: Proceedings of the 2023 ACM International Conference on Multimedia Retrieval
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URL

https://dl.acm.org/doi/abs/10.1145/3591106.3592281
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