Title | ||
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Hyperlocal: inferring location of IP addresses in real-time bid requests for mobile ads |
Abstract | ||
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To conduct a successful targeting campaign in mobile advertising, one needs to have reliable location information from real-time bid requests. However, many real-time bid requests do not include fine-grained location information (such as latitude and longitude) because (1) the device or the application did not collect that information or (2) some components of the real-time bid ecosystem did not forward that information. In this paper, we present a three-step approach that takes as input hashed public IP addresses in real-time bid requests and (1) creates a weighted heterogenous network, (2) applies network-inference techniques to infer fine-grain (but possibly noisy) location information for the hashed public IPs, and (3) uses k-nearest neighbor and census data to assign census block group IDs to those hashed public IPs. Our experiments on two large real-world datasets show the accuracy of our approach to be over 74% for hashed IPs (regardless of their type: mobile or non-mobile) when basing the inference on only hashed public mobile IPs. This is notable since our inference is over 212K possibilities. |
Year | DOI | Venue |
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2013 | 10.1145/2536689.2536807 | LBSN |
Keywords | Field | DocType |
public mobile ips,public ip address,reliable location information,fine-grained location information,real-time bid request,hashed ips,inferring location,location information,real-time bid ecosystem,hashed public ips,mobile advertising,location based services | Data mining,World Wide Web,Internet privacy,Hyperlocal,Inference,Computer science,Geographic coordinate system,Location-based service,Mobile advertising | Conference |
Citations | PageRank | References |
1 | 0.36 | 11 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Long Thanh Le | 1 | 39 | 4.96 |
Tina Eliassi-Rad | 2 | 1597 | 108.63 |
Foster J. Provost | 3 | 5427 | 740.79 |
Lauren Moores | 4 | 1 | 0.36 |