Abstract
Combining self-reports in which individuals reflect on their thoughts and feelings (Experience Samples) with sensor data collected via ubiquitous monitoring can provide researchers and applications with detailed insights about human behavior and psychology. However, meaningfully associating these two sources of data with each other is difficult: while it is natural for human beings to reflect on their experience in terms of remembered episodes, it is an open
challenge to retrace this subjective organization in sensor data
referencing objective time. Lifelogging is a specific approach to the ubiquitous monitoring of individuals that can contribute to overcoming this recollection gap. It strives to create a comprehensive timeline of semantic annotations that reflect the impressions of the monitored person from his or her own subjective point-of-view. In this paper, we describe a novel approach for processing such lifelogs to situate remembered experiences in an objective timeline. It involves the computational modeling of individuals’ memory processes to estimate segments within a lifelog acting as plausible digital representations for their recollections. We report about an empirical investigation in which we use our approach to discover plausible representations for remembered social interactions between participants in a longitudinal study. In particular, we describe an exploration of the behavior displayed by our model for memory processes in this setting. Finally, we explore the representations discovered for this study and discuss insights that might be gained from them.
challenge to retrace this subjective organization in sensor data
referencing objective time. Lifelogging is a specific approach to the ubiquitous monitoring of individuals that can contribute to overcoming this recollection gap. It strives to create a comprehensive timeline of semantic annotations that reflect the impressions of the monitored person from his or her own subjective point-of-view. In this paper, we describe a novel approach for processing such lifelogs to situate remembered experiences in an objective timeline. It involves the computational modeling of individuals’ memory processes to estimate segments within a lifelog acting as plausible digital representations for their recollections. We report about an empirical investigation in which we use our approach to discover plausible representations for remembered social interactions between participants in a longitudinal study. In particular, we describe an exploration of the behavior displayed by our model for memory processes in this setting. Finally, we explore the representations discovered for this study and discuss insights that might be gained from them.
Original language | English |
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Title of host publication | Proceedings of the Workshop on Modeling Cognitive Processes from Multimodal Data, MCPMD'18 |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery (ACM) |
Pages | 1-9 |
Number of pages | 9 |
ISBN (Electronic) | 978-1-4503-6072-2 |
DOIs | |
Publication status | Published - 2018 |
Event | MCPMD 2018: Workshop on Modeling Cognitive Processes from Multimodal Data - Boulder, CO, United States Duration: 16 Oct 2018 → 18 Oct 2018 |
Workshop
Workshop | MCPMD 2018 |
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Country/Territory | United States |
City | Boulder, CO |
Period | 16/10/18 → 18/10/18 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.