Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data

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...

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Main Authors: Meng Huang, Zhixiang Fang, Shili Xiong, Tao Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8664576/
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author Meng Huang
Zhixiang Fang
Shili Xiong
Tao Zhang
author_facet Meng Huang
Zhixiang Fang
Shili Xiong
Tao Zhang
author_sort Meng Huang
collection DOAJ
description 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 to fill 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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spelling doaj.art-5eedfb285da94394b3ada947842ad8a32022-12-21T23:25:34ZengIEEEIEEE Access2169-35362019-01-017308783088910.1109/ACCESS.2019.29032778664576Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone DataMeng Huang0https://orcid.org/0000-0001-9654-6195Zhixiang Fang1Shili Xiong2Tao Zhang3State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaDepartment of Advertising, University of Illinois at Urbana-Champaign, Urbana, IL, USAChina Mobile Group Hubei Company Limited, Wuhan, ChinaThe 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 to fill 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.https://ieeexplore.ieee.org/document/8664576/Interest-driven outdoor advertisingmaximal covering location problemmobile phone data
spellingShingle Meng Huang
Zhixiang Fang
Shili Xiong
Tao Zhang
Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data
IEEE Access
Interest-driven outdoor advertising
maximal covering location problem
mobile phone data
title Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data
title_full Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data
title_fullStr Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data
title_full_unstemmed Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data
title_short Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data
title_sort interest driven outdoor advertising display location selection using mobile phone data
topic Interest-driven outdoor advertising
maximal covering location problem
mobile phone data
url https://ieeexplore.ieee.org/document/8664576/
work_keys_str_mv AT menghuang interestdrivenoutdooradvertisingdisplaylocationselectionusingmobilephonedata
AT zhixiangfang interestdrivenoutdooradvertisingdisplaylocationselectionusingmobilephonedata
AT shilixiong interestdrivenoutdooradvertisingdisplaylocationselectionusingmobilephonedata
AT taozhang interestdrivenoutdooradvertisingdisplaylocationselectionusingmobilephonedata