Conference item
Towards better models of externalities in sponsored search auctions
- Abstract:
- Sponsored Search Auctions (SSAs) arguably represent the problem at the intersection of computer science and economics with the deepest applications in real life. Within the realm of SSAs, the study of the effects that showing one ad has on the other ads, a.k.a. externalities in economics, is of utmost importance and has so far attracted the attention of much research. However, even the basic question of modeling the problem has so far escaped a definitive answer. The popular cascade model is arguably too idealized to really describe the phenomenon yet it allows a good comprehension of the problem. Other models, instead, describe the setting more adequately but are too complex to permit a satisfactory theoretical analysis. In this work, we attempt to get the best of both approaches: firstly, we define a number of general mathematical formulations for the problem in the attempt to have a rich description of externalities in SSAs and, secondly, prove a host of results drawing a nearly complete picture about the computational complexity of the problem. We complement these approximability results with some considerations about mechanism design in our context.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 337.0KB, Terms of use)
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- Publisher copy:
- 10.3233/978-1-61499-672-9-1167
Authors
- Publisher:
- IOS Press
- Host title:
- ECAI 2016
- Journal:
- ECAI 2016 More from this journal
- Volume:
- 285
- Pages:
- 1167-1175
- Series:
- Frontiers in Artificial Intelligence and Applications
- Publication date:
- 2016-09-02
- Acceptance date:
- 2016-06-07
- DOI:
- EISSN:
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1879-8314
- ISSN:
-
0922-6389
- ISBN:
- 9781614996729
- Keywords:
- Pubs id:
-
pubs:974864
- UUID:
-
uuid:a6fc74a8-8f4f-4f67-a0d0-09f13c93d0dd
- Local pid:
-
pubs:974864
- Source identifiers:
-
974864
- Deposit date:
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2019-02-20
- ARK identifier:
Terms of use
- Copyright holder:
- Gatti et al
- Copyright date:
- 2016
- Notes:
-
Copyright © 2016 The Authors and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
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