Projects per year
Abstract
How assessors and end users judge the relevance of images has been studied in information science and information retrieval for a considerable time. The criteria by which assessors' judge relevance has been intensively studied, and there has been a large amount of work which has investigated how relevance judgments for test collections can be more cheaply generated, such as through crowd sourcing. Relatively little work has investigated the process individual assessors go through to judge the relevance of an image. In this paper, we focus on the process by which relevance is judged for images, and in particular, the degree of effort a user must expend to judge relevance for different topics. Results suggest that topic difficulty and how semantic/visual a topic is impact user performance and perceived effort.
Original language | English |
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Title of host publication | Proceedings of the 37th international ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR '14) |
Place of Publication | New York, NY, United States |
Pages | 887-890 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 31 Jul 2014 |
Event | 37th International ACM SIGIR Conference on Research and Development in Information Retrieval - Gold Coast, Australia Duration: 6 Jul 2014 → 11 Jul 2014 |
Conference
Conference | 37th International ACM SIGIR Conference on Research and Development in Information Retrieval |
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Abbreviated title | SIGIR '14 |
Country/Territory | Australia |
Period | 6/07/14 → 11/07/14 |
Keywords
- information retrieval
- relevance judgements
- image retrieval
- image
- judgment
- relevance
- effort
- assessment
Fingerprint
Dive into the research topics of 'Evaluating the effort involved in relevance assessments for images'. Together they form a unique fingerprint.Projects
- 1 Finished
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Understanding the annotation process: annotation for Big Data
AHRC (Arts and Humanities Research Council)
1/08/14 → 30/06/15
Project: Research
Datasets
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Evaluating the effort involved in relevance assessments for images
Halvey, M. (Creator) & Villa, R. (Creator), University of Strathclyde, 9 Jul 2015
DOI: 10.15129/8b8e3b9d-aa89-41e4-89d0-59b40d0bf1f3
Dataset