Nguyen, Thao-Nhu ORCID: 0000-0003-1356-9434, Le, Tu-Khiem ORCID: 0000-0003-3013-9380, Ninh, Van-Tu, Tran, Ly-Duyen, Nguyen, Manh-Duy, Tran, Minh-Triet ORCID: 0000-0003-3046-3041, Nguyen, Binh T., Caputo, Annalina ORCID: 0000-0002-7144-8545, Gurrin, Cathal ORCID: 0000-0003-2903-3968, Healy, Graham ORCID: 0000-0001-6429-6339 and Smyth, Sinéad ORCID: 0000-0002-8736-0505 (2022) DCU and HCMUS at NTCIR-16 Lifelog-4. In: 16th Conference on Evaluation of Information Access Technologies (NTCIR 16), 14-17 June 2022, Tokyo, Japan.
Abstract
In this paper, we present our DCU and HCMUS team’s participation in the NTCIR16 Lifelog-4 task by using two different retrieval
systems, namely LifeSeeker and Myscéal that were originally introduced in the Lifelog Search Challenge (LSC) and adapted for
addressing the Lifelog Semantic Access Task (LSAT). To tackle the
task in an automatic manner, both LifeSeeker and Myscéal employed pre-processing techniques as part of the retrieval process,
while LifeSeeker further utilised a post-processing step to refine the
retrieval results. Regarding the interactive manner, we evaluated the
Myscéal system by conducting a user study on both expert and
novice users in both ad-hoc and known-item-search settings.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Subjects: | Computer Science > Information retrieval Computer Science > Multimedia systems Computer Science > Lifelog |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > INSIGHT Centre for Data Analytics Research Initiatives and Centres > ADAPT |
Published in: | Proceedings of the 16th NTCIR Conference on Evaluation of Information Access Technologies. . NTCIR. |
Publisher: | NTCIR |
Official URL: | https://research.nii.ac.jp/ntcir/workshop/OnlinePr... |
Copyright Information: | © 2022 The Authors |
Funders: | Irish Research Council (IRC) under Grant Number GOIPG/2016/741, Science Foundation Ireland grant numbers 13/RC/2106, 13/RC/2106_P2, SFI/12/RC/2289_P2, 18/CRT/6223, 18/CRT/6224 and SFI/13/RC/2106_P2 and co-funded by the European Regional Development Fund, Insight SFI Research Centre for Data Analytics, ADAPT - Centre for Digital Content Technology, European Regional Development Fund |
ID Code: | 26429 |
Deposited On: | 21 Jul 2022 11:46 by Thao-Nhu Nguyen . Last Modified 08 Sep 2022 14:19 |
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