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.
- Daniel Chaffin, Ralph Heidl, John R Hollenbeck, Michael Howe, Andrew Yu, Clay Voorhees, and Roger Calantone. 2017. The Promise and Perils of Wearable Sensors in Organizational Research. Organizational Research Methods 20, 1 (jan 2017), 3--31.Google ScholarCross Ref
- Tanzeem Choudhury and Alex (Sandy) Pentland. 2002. The sociometer: A wearable device for understanding human networks. CSCW'02 Workshop: Ad hoc Communications and Collaboration in Ubiquitous Computing Environments, New Orleans, Louisiana, USA (2002).Google Scholar
- David Clewett and Lila Davachi. 2017. The ebb and flow of experience determines the temporal structure of memory. Current Opinion in Behavioral Sciences 17 (oct 2017), 186--193.Google Scholar
- Martin A. Conway. 2009. Episodic memories. Neuropsychologia 47, 11 (sep 2009), 2305--2313.Google ScholarCross Ref
- Martin A Conway and Christopher W Pleydell-Pearce. 2000. The construction of autobiographical memories in the self-memory system. Psychological Review 107, 2 (apr 2000), 261--288.Google ScholarCross Ref
- Aiden R. Doherty and Alan F. Smeaton. 2008. Combining face detection and novelty to identify important events in a visual lifelog. Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008 (2008), 348--353. Google ScholarDigital Library
- Aiden R Doherty, Alan F Smeaton, Keansub Lee, and Daniel P W Ellis. 2007. Multimodal segmentation of lifelog data. RIAO 2007 LargeScale Semantic Access to Content Text Image Video and Sound 2006 (2007), 21--38. Google ScholarDigital Library
- Simon Farrell. 2012. Temporal clustering and sequencing in short-term memory and episodic memory. Psychological Review 119, 2 (apr 2012), 223--271.Google Scholar
- Cathal Gurrin, Alan F. Smeaton, and Aiden R. Doherty. 2014. LifeLogging: Personal Big Data. Foundations and Trends® in Information Retrieval 8, 1 (2014), 1--125. Google ScholarDigital Library
- Cathal Gurrin, Alan F. Smeaton, Zhengwei Qiu, and Aiden Doherty. 2013. Exploring the technical challenges of large-scale lifelogging. In Proceedings of the 4th International SenseCam & Pervasive Imaging Conference on - SenseCam '13. ACM Press, New York, New York, USA, 68--75. Google ScholarDigital Library
- Steve W J Kozlowski, Georgia T Chao, Chu Hsiang Chang, and Rosemarie Fernandez. 2015. Big Data at Work. Routledge. 272--309 pages.Google Scholar
- Jean-Philippe P Laurenceau, Lisa Feldman Barrett, and Paula R. Pietromonaco. 1998. Intimacy as an interpersonal process: the importance of self-disclosure, partner disclosure, and perceived partner responsiveness in interpersonal exchanges. Journal of personality and social psychology 74, 5 (may 1998), 1238--51.Google ScholarCross Ref
- Matthew L. Lee and Anind K. Dey. 2008. Lifelogging memory appliance for people with episodic memory impairment. In Proceedings of the 10th international conference on Ubiquitous computing - UbiComp '08, Vol. 344. ACM Press, New York, New York, USA, 44. Google ScholarDigital Library
- Christie Napa Scollon, Chu-Kim Prieto, and Ed Diener. 2009. Experience Sampling: Promises and Pitfalls, Strength and Weaknesses. In Assessing Well-Being: The Collected Works of Ed Diener, Ed Diener (Ed.). Vol. 4. Springer, Dordrecht, 157--180.Google Scholar
- Claudia Roda and Julie Thomas. 2006. Attention aware systems: Theories, applications, and research agenda. Computers in Human Behavior 22, 4 (jul 2006), 557--587.Google ScholarCross Ref
- Eduardo Salas, Rebecca Grossman, Ashley M. Hughes, and Chris W. Coultas. 2015. Measuring Team Cohesion: Observations from the Science. Human Factors: The Journal of the Human Factors and Ergonomics Society 57, 3 (may 2015), 365--374.Google ScholarCross Ref
- Saul Shiffman, Michael Hufford, Mary Hickcox, Jean A Paty, Maryann Gnys, and Jon D Kassel. 1997. Remember that? A comparison of real-time versus retrospective recall of smoking lapses. Journal of Consulting and Clinical Psychology 65, 2 (apr 1997), 292--300.Google ScholarCross Ref
- Estefania Talavera, Mariella Dimiccoli, Marc Bolaños, Maedeh Aghaei, and Petia Radeva. 2015. R-Clustering for Egocentric Video Segmentation. In Pattern Recognition and Image Analysis, Paredes R., Cardoso J., and Pardo X (Eds.). Springer International Publishing, 327--336.Google Scholar
- Endel Tulving. 2002. Episodic Memory: From Mind to Brain. Annual Review of Psychology 53, 1 (feb 2002), 1--25.Google ScholarCross Ref
- Peng Wang and Alan F. Smeaton. 2011. Aggregating semantic concepts for event representation in lifelogging. In Proceedings of the International Workshop on Semantic Web Information Management - SWIM '11. ACM Press, New York, New York, USA, 1--6. Google ScholarDigital Library
- Yanxia Zhang, Jeffrey Olenick, Chu-Hsiang Chang, Steve W J Kozlowski, and Hayley Hung. 2018. The I in Team. In Proceedings of the 2018 Conference on Human Information Interaction&Retrieval - IUI '18 (IUI '18). ACM Press, New York, New York, USA, 421--426. Google ScholarDigital Library
Index Terms
- Discovering digital representations for remembered episodes from lifelog data
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