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초록
In recent years, large-scale data collection has become crucial in Human-Computer Interaction (HCI) research. With a sharp climb of the amount of data being gathered due to an increasing number of mobile and wearable devices, real-time maintenance of Data Quality (DQ) of data-collection campaigns has already become an overwhelming task, especially in large-scale experiments. This paper proposes EasyTrack, a platform that collects large-scale data in an automatized manner. We describe how our proposed solution detects and tackles issues in data collection campaigns in an automated manner. © 2019 Copyright held by the owner/author(s).
키워드
Data Quality; Human-Centered Computing; Human-Computer Interaction; Streaming Sensor Data; User studies; Wearable Devices
- 제목
- EasyTrack - Orchestrating large-scale mobile user experimental studies
- 저자
- Toshnazarov, Kobiljon; Baazizi, Hamza; Narziev, Nematjon; Noh, Youngtae; Lee, Uichin
- 발행일
- 2019
- 유형
- Conference paper
- 저널명
- MobiSys 2019 - Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services
- 페이지
- 576 ~ 577