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Nameles: An intelligent system for Real-Time Filtering of Invalid Ad Traffic
dc.contributor.author | Pastor, Antonio | |
dc.contributor.author | Pärssinen, Matti | |
dc.contributor.author | Callejo, Patricia | |
dc.contributor.author | Vallina, Pelayo | |
dc.contributor.author | Cuevas, Rubén | |
dc.contributor.author | Cuevas, Ángel | |
dc.contributor.author | Kotila, Mikko | |
dc.contributor.author | Azcorra, Arturo | |
dc.date.accessioned | 2021-07-13T09:37:37Z | |
dc.date.available | 2021-07-13T09:37:37Z | |
dc.date.issued | 2019-05-13 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12761/688 | |
dc.description.abstract | Invalid ad traffic is an inherent problem of programmatic advertising that has not been properly addressed so far. Traditionally, it has been considered that invalid ad traffic only harms the interests of advertisers, which pay for the cost of invalid ad impressions while other industry stakeholders earn revenue through commissions regardless of the quality of the impression. Our first contribution consists of providing evidence that shows how the Demand Side Platforms (DSPs), one of the most important intermediaries in the programmatic advertising supply chain, may be suffering from economic losses due to invalid ad traffic. Addressing the problem of invalid traffic at DSPs requires a highly scalable solution that can identify invalid traffic in real time at the individual bid request level. The second and main contribution is the design and implementation of a solution for the invalid traffic problem, a system that can be seamlessly integrated into the current programmatic ecosystem by the DSPs. Our system has been released under an open source license, becoming the first auditable solution for invalid ad traffic detection. The intrinsic transparency of our solution along with the good results obtained in industrial trials have led the World Federation of Advertisers to endorse it. | |
dc.language.iso | eng | |
dc.title | Nameles: An intelligent system for Real-Time Filtering of Invalid Ad Traffic | en |
dc.type | conference object | |
dc.conference.date | 13-17 May 2019 | |
dc.conference.place | San Francisco, CA, USA | |
dc.conference.title | The Web Conference 2019 (WWW 2019) | * |
dc.event.type | conference | |
dc.pres.type | paper | |
dc.type.hasVersion | VoR | |
dc.rights.accessRights | open access | |
dc.description.refereed | TRUE | |
dc.description.status | pub | |
dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/1964 |