Intelligent Task Recognition: Towards Enabling Productivity Assistance in Daily Life

  • Jonathan Liono ,
  • Mohammad Saiedur Rahaman ,
  • Flora D Salim ,
  • Yongli Ren ,
  • Damiano Spina ,
  • Falk Scholer ,
  • Johanne R Trippas ,
  • Mark Sanderson ,
  • ,
  • Paul Bennett

2020 International Conference on Multimedia Retrieval |

Télécharger BibTex

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 (CPS) 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 real-world 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 work-related tasks.