The modern outdoor advertising industry is introducing new technologies to attract attention and enhance effective reach. However, displaying the pertinent advertisements (ads) and maximizing their coverage are still a challenge, as little is known about the interests of passersby. In this paper, we attempted toll this gap by 1) identifying the individuals' interests extracted from the mobile phone internet usage data,and 2) analyzing the individuals' mobility patterns acquired from the mobile phone location data. Based on these data, the problem of distributing the outdoor ads to the maximum reach of the potentially interested users was further formulated as a maximal covering location problem (MCLP). Specifically, a continuous space maximal coverage model, the MCLP-complementary coverage (MCLP-CC), was utilized to search for the optimal locations for a given category of advertisements. Finally, the proposed methodology was applied to Wuxue, a city in central China, as a case study. The calculation results show that when setting the same number of places for outdoor advertising, our approach achieves an average of 69% improvement compared with the current dominant ads placement approach (selecting the most crowded location) in reaching the potential target audiences. An average of 15% improvement compared with the classic MCLP model.Overall, this paper demonstrates the value of the mobile phone data for interest-driven outdoor advertising and its potential applications in other mobile services.
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