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Ruben Verborgh

EcoDaLo: Federating Advertisement Targeting with Linked Data

Sven Lieber, Ben De Meester, Ruben Verborgh, and Anastasia Dimou

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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Published in 2020 in Proceedings of the 16th International Conference on Semantic Systems.

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Cite this article easily using its BibTeX entry: 

@inproceedings{lieber_semantics_2020,
  author = {Lieber, Sven and De Meester, Ben and Verborgh, Ruben and Dimou, Anastasia},
  title = {{EcoDaLo:} Federating Advertisement Targeting with {Linked Data}},
  booktitle = {Proceedings of the 16th International Conference on Semantic Systems},
  year = 2020,
  month = sep,
  pages = {87--103},
  volume = 12378,
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-59833-4},
  doi = {10.1007/978-3-030-59833-4_6},
  url = {https://link.springer.com/content/pdf/10.1007%2F978-3-030-59833-4_6.pdf},
}

Alternatively, pick a reference of your choice below:

ACM
Sven Lieber, Ben De Meester, Ruben Verborgh, and Anastasia Dimou. 2020. EcoDaLo: Federating Advertisement Targeting with Linked Data. In Proceedings of the 16th International Conference on Semantic Systems (Lecture Notes in Computer Science), Springer, 87–103.
APA
Lieber, S., De Meester, B., Verborgh, R., & Dimou, A. (2020). EcoDaLo: Federating Advertisement Targeting with Linked Data. Proceedings of the 16th International Conference on Semantic Systems, 12378, 87–103.
IEEE
S. Lieber, B. De Meester, R. Verborgh, and A. Dimou, “EcoDaLo: Federating Advertisement Targeting with Linked Data,” in Proceedings of the 16th International Conference on Semantic Systems, 2020, vol. 12378, pp. 87–103.
LNCS
Lieber, S., De Meester, B., Verborgh, R., Dimou, A.: EcoDaLo: Federating Advertisement Targeting with Linked Data. In: Proceedings of the 16th International Conference on Semantic Systems. pp. 87–103. Springer (2020).
MLA
Lieber, Sven, et al. “EcoDaLo: Federating Advertisement Targeting with Linked Data.” Proceedings of the 16th International Conference on Semantic Systems, vol. 12378, Springer, 2020, pp. 87–103.

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