Intelligent Task Recognition: Towards Enabling Productivity Assistancein Daily Life

Publication Year: 2020 Publication Type : ConferenceProceeding

Abstract:


We introduce the novel research problem of task recognition in daily life.We recognize tasks such as project management, planning, meal-breaks, communication, documentation, and family care. We capture Cyber, Physical, and Social (CSP) activities of 17 participants over four weeks using device-based sensing, app activity logging, and an experience sampling methodology. Our cohort includes students, casual workers, and professionals, forming the first realworld context-rich task behaviour dataset. We model CPS activities across different task categories, results highlight the importance of considering the CPS feature sets in modelling, especially workrelated tasks.


BibTex:

@inproceedings{DBLP:conf/mir/LionoRSRSSTSBW20,
    author = {Jonathan Liono and Mohammad Saiedur Rahaman and Flora D. Salim and Yongli Ren and Damiano Spina and Falk Scholer and Johanne R. Trippas and Mark Sanderson and Paul N. Bennett and Ryen W. White},
    bibsource = {dblp computer science bibliography, https://dblp.org},
    biburl = {https://dblp.org/rec/conf/mir/LionoRSRSSTSBW20.bib},
    booktitle = {Proceedings of the 2020 on International Conference on Multimedia Retrieval, ICMR 2020, Dublin, Ireland, June 8-11, 2020},
    doi = {10.1145/3372278.3390703},
    editor = {Cathal Gurrin and Björn Þór Jónsson and Noriko Kando and Klaus Schöffmann and Yi-Ping Phoebe Chen and Noel E. O'Connor},
    pages = {472--478},
    publisher = {ACM},
    timestamp = {Sun, 14 Jun 2020 12:18:46 +0200},
    title = {Intelligent Task Recognition: Towards Enabling Productivity Assistance in Daily Life},
    url = {https://doi.org/10.1145/3372278.3390703},
    year = {2020}
}

Cite:

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