Abstract
Crowdphotographing, an emerging self-service mode over the mobile Internet, is to recruit several users to take the pictures via incentive mechanism. Importantly, it can be used for business inspection and information collection for enterprises. This paper mainly studies the rationality and optimization of task pricing for crowdphotographing. In this paper, different multivariate linear regression models are established to analyze the task pricing, performance, membership information and so forth. The multivariate linear regression equation is eventually obtained, which efficiently solves the problem of task pricing.
This research was supported by the National Natural Science Foundation of China (Grant No. 61702317), MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-2014-1-00720) supervised by the IITP (Institute for Information & communications Technology Promotion) and the National Research Foundation of Korea (No. 2017R1A2B1008421) and was also supported by the Fundamental Research Funds for the Central Universities, China (GK201703059).
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Hao, F., Guo, H., Park, DS. (2020). A Framework for Learning the Pricing Model of Sensing Tasks in Crowdphotographing. In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_105
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DOI: https://doi.org/10.1007/978-981-13-9341-9_105
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