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Rethinking the test collection methodology for personal self-tracking data

Hopfgartner, Frank orcid logoORCID: 0000-0003-0380-6088, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 and Joho, Hideo (2019) Rethinking the test collection methodology for personal self-tracking data. In: International Conference on Multimedia Modeling (MMM 2020), 5-8 Jan 2020, Daejeon, Korea. ISBN 978-3-030-37733-5

Abstract
While vast volumes of personal data are being gathered daily by individuals, the MMM community has not really been tackling the challenge of developing novel retrieval algorithms for this data, due to the challenges of getting access to the data in the first place. While initial efforts have taken place on a small scale, it is our conjecture that a new evaluation paradigm is required in order to make progress in analysing, modeling and retrieving from personal data archives. In this position paper, we propose a new model of Evaluation-as-a-Service that re-imagines the test collection methodology for personal multimedia data in order to address the many challenges of releasing test collections of personal multimedia data.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:evaluation; self-tracking
Subjects:Computer Science > Information retrieval
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: MultiMedia Modeling. MMM 2020, Proceedings. Lecture Notes in Computer Science (LNCS) 11962. Springer International Publishing. ISBN 978-3-030-37733-5
Publisher:Springer International Publishing
Official URL:http://dx.doi.org/10.1007/978-3-030-37734-2_38
Copyright Information:© 2019 Springer
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:24196
Deposited On:10 Feb 2020 09:47 by Cathal Gurrin . Last Modified 15 Dec 2021 15:44
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