NDLI: Whole-Page Optimization and Submodular Welfare Maximization with Online Bidders

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Whole-Page Optimization and Submodular Welfare Maximization with Online Bidders

Content Provider	ACM Digital Library
Author	Devanur, Nikhil R. Yan, Qiqi Mirrokni, Vahab S. Huang, Zhiyi Korula, Nitish
Copyright Year	2016
Abstract	In the context of online ad serving, display ads may appear on different types of $web\textit{pages},$ where each page includes $\textit{several}$ ad slots and therefore multiple ads can be shown on each page. The set of ads that can be assigned to ad slots of the same page needs to satisfy various prespecified constraints including exclusion constraints, diversity constraints, and the like. Upon arrival of a user, the ad serving system needs to allocate a set of ads to the current webpage respecting these per-page allocation constraints. Previous slot-based settings ignore the important concept of a page and may lead to highly suboptimal results in general. In this article, motivated by these applications in display advertising and inspired by the submodular welfare maximization problem with online bidders, we study a general class of page-based ad allocation problems, present the first (tight) constant-factor approximation algorithms for these problems, and confirm the performance of our algorithms experimentally on real-world datasets. A key technical ingredient of our results is a novel primal-dual analysis for handling free disposal, which updates dual variables using a “level function” instead of a single level and unifies with previous analyses of related problems. This new analysis method allows us to handle arbitrarily complicated allocation constraints for each page. Our main result is an algorithm that achieves a 1 &minus frac 1 e &minus $\textit{o}(1)-competitive$ ratio. Moreover, our experiments on real-world datasets show significant improvements of our page-based algorithms compared to the slot-based algorithms. Finally, we observe that our problem is closely related to the submodular welfare maximization (SWM) problem. In particular, we introduce a variant of the SWM problem with online bidders and show how to solve this problem using our algorithm for whole-page optimization.
Starting Page	1
Ending Page	20
Page Count	20
File Format	PDF
ISSN	21678375
e-ISSN	21678383
DOI	10.1145/2892563
Volume Number	4
Issue Number	3
Journal	ACM Transactions on Economics and Computation (TEAC)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-04-06
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Wireless sensor networks Media access control Multichannel Radio interference Time synchronization
Content Type	Text
Resource Type	Article
Subject	Economics and Econometrics Marketing Computational Mathematics Statistics and Probability Computer Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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