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For service usage data we consider five services: web domain visit (web), application (app), email, voice call (call), and short message service (SMS).
User U3 wants to cut down the expenses for service usage, and his personal context information shows that he tends to make an economy choice.
Service incentive is a non-monetary reward system wherein participants in mobile crowdsensing systems are asked to contribute sensed data in return for service usage [1].
Given the aggregate durations for different contexts obtained in the Section 3, this finding can be explained such that the longer duration for some context means the higher chance for service usage.
Frequencies, means and standard deviations were used descriptively according to the level of the variable for service usage, vascular complications and potential predictive factors.
Moreover, ways to identify the dying early in their trajectory were limited and so the median time to death for service usage was 6 20 days [ 10].
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Understanding well service platform business processes and scenarios is equally important for realistic modeling of service usage, delivery and provision.
Our findings on the spatiotemporal correlations of service usage patterns for different contexts enable us to better understand the behavior of humans and what that implies.
Service cost represents the price for every service usage.
The spatiotemporal correlation of service usages for user i is fully characterized by the number of events corresponding to the service s in the cell c and at time t, denoted by n i s ( c, t ).
Contextual correlations of service usages are measured for users 5 and 81 and for all users (from top to bottom).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com