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EcoDaLo: Federating Advertisement Targeting with Linked Data

A key source of revenue for the media and entertainment domain is ad targeting: serving advertisements to a select set of visitors based on various captured visitor traits. Compared to global media companies such as Google and Facebook that aggregate data from various sources (and the privacy concer...

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Detalles Bibliográficos
Autores principales: Lieber, Sven, De Meester, Ben, Verborgh, Ruben, Dimou, Anastasia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586443/
http://dx.doi.org/10.1007/978-3-030-59833-4_6
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author Lieber, Sven
De Meester, Ben
Verborgh, Ruben
Dimou, Anastasia
author_facet Lieber, Sven
De Meester, Ben
Verborgh, Ruben
Dimou, Anastasia
author_sort Lieber, Sven
collection PubMed
description A key source of revenue for the media and entertainment domain is ad targeting: serving advertisements to a select set of visitors based on various captured visitor traits. Compared to global media companies such as Google and Facebook that aggregate data from various sources (and the privacy concerns these aggregations bring), local companies only capture a small number of (high-quality) traits and retrieve an unbalanced small amount of revenue. To increase these local publishers’ competitive advantage, they need to join forces, whilst taking the visitors’ privacy concerns into account. The EcoDaLo consortium, located in Belgium and consisting of Adlogix, Pebble Media, and Roularta Media Group as founding partners, aims to combine local publishers’ data without requiring these partners to share this data across the consortium. Usage of Semantic Web technologies enables a decentralized approach where federated querying allows local companies to combine their captured visitor traits, and better target visitors, without aggregating all data. To increase potential uptake, technical complexity to join this consortium is kept minimal, and established technology is used where possible. This solution was showcased in Belgium which provided the participating partners valuable insights and suggests future research challenges. Perspectives are to enlarge the consortium and provide measurable impact in ad targeting to local publishers.
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spelling pubmed-75864432020-10-27 EcoDaLo: Federating Advertisement Targeting with Linked Data Lieber, Sven De Meester, Ben Verborgh, Ruben Dimou, Anastasia Semantic Systems. In the Era of Knowledge Graphs Article A key source of revenue for the media and entertainment domain is ad targeting: serving advertisements to a select set of visitors based on various captured visitor traits. Compared to global media companies such as Google and Facebook that aggregate data from various sources (and the privacy concerns these aggregations bring), local companies only capture a small number of (high-quality) traits and retrieve an unbalanced small amount of revenue. To increase these local publishers’ competitive advantage, they need to join forces, whilst taking the visitors’ privacy concerns into account. The EcoDaLo consortium, located in Belgium and consisting of Adlogix, Pebble Media, and Roularta Media Group as founding partners, aims to combine local publishers’ data without requiring these partners to share this data across the consortium. Usage of Semantic Web technologies enables a decentralized approach where federated querying allows local companies to combine their captured visitor traits, and better target visitors, without aggregating all data. To increase potential uptake, technical complexity to join this consortium is kept minimal, and established technology is used where possible. This solution was showcased in Belgium which provided the participating partners valuable insights and suggests future research challenges. Perspectives are to enlarge the consortium and provide measurable impact in ad targeting to local publishers. 2020-10-27 /pmc/articles/PMC7586443/ http://dx.doi.org/10.1007/978-3-030-59833-4_6 Text en © The Author(s) 2020 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
spellingShingle Article
Lieber, Sven
De Meester, Ben
Verborgh, Ruben
Dimou, Anastasia
EcoDaLo: Federating Advertisement Targeting with Linked Data
title EcoDaLo: Federating Advertisement Targeting with Linked Data
title_full EcoDaLo: Federating Advertisement Targeting with Linked Data
title_fullStr EcoDaLo: Federating Advertisement Targeting with Linked Data
title_full_unstemmed EcoDaLo: Federating Advertisement Targeting with Linked Data
title_short EcoDaLo: Federating Advertisement Targeting with Linked Data
title_sort ecodalo: federating advertisement targeting with linked data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586443/
http://dx.doi.org/10.1007/978-3-030-59833-4_6
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