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MemoriEase 2.0: A Conversational Lifelog Retrieve System for LSC'24

Tran, Quang-Linh orcid logoORCID: 0000-0002-5409-0916, Nguyen, Binh, Jones, Gareth J. F. orcid logoORCID: 0000-0003-2923-8365 and Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 (2024) MemoriEase 2.0: A Conversational Lifelog Retrieve System for LSC'24. In: 7th Annual ACM Workshop on the Lifelog Search Challenge. ISBN 9798400705502

Abstract
Lifelog retrieval plays an important role in memory support for lifeloggers. It helps the lifeloggers to browse, search and navigate their life moments from the lifelog data. However, the volume and variety of lifelog data are enormous and range in multiple modalities so they impose a big challenge to retrieve accurate lifelog moments. The Lifelog Search Challenges (LSCs) are a benchmark challenge for evaluating lifelog retrieval systems in different tasks. In this paper, we introduce the MemoriEase 2.0 lifelog retrieval system that participates in LSC'24. This system not only inherits core functions from the precedent system but also incorporates new components such as conversational search, visual similarity search and retrieval-augmented generation for question-answering tasks. The new functions are expected to help expert and novice users solve all topics in three tasks of LSC'24. We evaluate MemoriEase 2.0 in KIS topics in LSC'23 and the system achieves promising results with Recall@1 is 40% at the first hint and it solves 8 over 10 topics.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:lifelog retrieval, conversational search, personal archive
Subjects:Computer Science > Information retrieval
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Published in: LSC '24: Proceedings of the 7th Annual ACM Workshop on the Lifelog Search Challenge. . Association for Computing Machinery. ISBN 9798400705502
Publisher:Association for Computing Machinery
Official URL:https://dl.acm.org/doi/proceedings/10.1145/3643489
Copyright Information:Authors
Funders:ADAPT Centre
ID Code:30197
Deposited On:13 Aug 2024 11:17 by Linh Tran . Last Modified 13 Aug 2024 11:17
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