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Towards Activity Recommendation from Lifelogs
Date Issued
2014-12-06
Date Available
2017-04-28T09:56:12Z
Abstract
With the increasing availability of passive, wearable sensor devices, digital lifelogs can now be captured for individuals. Lifelogs contain a digital trace of a person’s life, and are characterised by large quantities of rich contextual data. In this paper, we propose a content based recommender system to leverage such lifelogs to suggest activities to users. We model lifelogs as timelines of chronological sequences of activity objects, and describe a recommendation framework in which a two-level distance metric is proposed to measure the similarity between current and past timelines. An initial evaluation of our activity recommender performed using a real-world lifelog dataset demonstrates the utility of our approach.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Start Page
87
End Page
96
Copyright (Published Version)
2014 ACM
Language
English
Status of Item
Peer reviewed
Conference Details
iiWAS '14: The 16th International Conference on Information Integration and Web-based Applications & Services (iiWAS2014), Hanoi, Vietnam, 4-6 December 2014
ISBN
9781450330015
This item is made available under a Creative Commons License
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Towards Activity Recommendation from Lifelogs.pdf
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899.63 KB
Format
Owning collection
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