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@inproceedings{Khwaja:2019:10.1145/3298689.3347020,
author = {Khwaja, M and Ferrer, M and Jesus, I and Faisal, A and Matic, A},
doi = {10.1145/3298689.3347020},
pages = {368--372},
publisher = {ACM},
title = {Aligning daily activities with personality: towards a recommender system for improving wellbeing},
url = {http://dx.doi.org/10.1145/3298689.3347020},
year = {2019}
}

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TY  - CPAPER
AB  - Recommender Systems have not been explored to a great extentfor improving health and subjective wellbeing. Recent advances inmobile technologies and user modelling present the opportunityfor delivering such systems, however the key issue is understand-ing the drivers of subjective wellbeing at an individual level. Inthis paper we propose a novel approach for deriving personalizedactivity recommendations to improve subjective wellbeing by maxi-mizing the congruence between activities and personality traits. Toevaluate the model, we leveraged a rich dataset collected in a smart-phone study, which contains three weeks of daily activity probes,the Big-Five personality questionnaire and subjective wellbeingsurveys. We show that the model correctly infers a range of activ-ities that are ’good’ or ’bad’ (i.e. that are positively or negativelyrelated to subjective wellbeing) for a given user and that the derivedrecommendations greatly match outcomes in the real-world.
AU  - Khwaja,M
AU  - Ferrer,M
AU  - Jesus,I
AU  - Faisal,A
AU  - Matic,A
DO  - 10.1145/3298689.3347020
EP  - 372
PB  - ACM
PY  - 2019///
SP  - 368
TI  - Aligning daily activities with personality: towards a recommender system for improving wellbeing
UR  - http://dx.doi.org/10.1145/3298689.3347020
UR  - https://recsys.acm.org/recsys19/
UR  - http://hdl.handle.net/10044/1/72160
ER  -

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Professor Aldo Faisal

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