Mobile Computing, Applications, and Services. 9th International Conference, MobiCASE 2018, Osaka, Japan, February 28 – March 2, 2018, Proceedings

Research Article

Gamification for High-Quality Dataset in Mobile Activity Recognition

  • @INPROCEEDINGS{10.1007/978-3-319-90740-6_14,
        author={Nattaya Mairittha and Sozo Inoue},
        title={Gamification for High-Quality Dataset in Mobile Activity Recognition},
        proceedings={Mobile Computing, Applications, and Services. 9th International Conference, MobiCASE 2018,  Osaka, Japan, February 28 -- March 2, 2018, Proceedings},
        proceedings_a={MOBICASE},
        year={2018},
        month={5},
        keywords={Mobile activity recognition Quality of dataset Gamification},
        doi={10.1007/978-3-319-90740-6_14}
    }
    
  • Nattaya Mairittha
    Sozo Inoue
    Year: 2018
    Gamification for High-Quality Dataset in Mobile Activity Recognition
    MOBICASE
    Springer
    DOI: 10.1007/978-3-319-90740-6_14
Nattaya Mairittha1,*, Sozo Inoue1,*
  • 1: Kyushu Institute of Technology
*Contact email: fah@sozolab.jp, sozo@sozolab.jp

Abstract

This paper presents a gamification concept for getting high-quality user-annotated datasets in the context of mobile activity recognition, as well as a cheating detection algorithm. The novel idea behind this concept is that users are motivated by getting feedback about the quality of their labeling activity as rewards or gamification element. For that, the collected sensor data and labels are used as training data for a machine learning algorithm for determining the dataset quality based on the resulting accuracy. By using the proposed method, the results show that the gamification elements increase the quantity (labels from the proposed method is higher than the naive by at least 305) and the quality (the accuracy of the proposed data outperformed the original data by at least 4.3%) of the labels. Besides, the cheating detection algorithm could detect cheating with the accuracy of more than 70% that is fascinating work.