New stochastic algorithms for scheduling ads in sponsored search

We introduce a family of algorithms for the selection of ads in sponsored search that intends to increase the variety of choices, while not significantly reducing revenue and maintaining an incentive for advertisers to keep their bids as high as possible. Diversification of ads may be convenient for...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Feuerstein, E., Martínez-Viademonte, J., Heiber, P.A., Baeza-Yates, R.
Formato:	CONF
Materias:	Commerce Image retrieval Click-through rates Price auctions Pricing mechanisms Stochastic algorithms Economics
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_07695300_v_n_p22_Feuerstein
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_07695300_v_n_p22_Feuerstein
record_format	dspace
spelling	todo:paper_07695300_v_n_p22_Feuerstein2023-10-03T15:39:44Z New stochastic algorithms for scheduling ads in sponsored search Feuerstein, E. Martínez-Viademonte, J. Heiber, P.A. Baeza-Yates, R. Commerce Image retrieval Click-through rates Price auctions Pricing mechanisms Stochastic algorithms Economics We introduce a family of algorithms for the selection of ads in sponsored search that intends to increase the variety of choices, while not significantly reducing revenue and maintaining an incentive for advertisers to keep their bids as high as possible. Diversification of ads may be convenient for many reasons, which we also expose. Our algorithms try to distribute the available slots among all ads, using a proportional mechanism based on the bids and the expected click-through rates of the ads. Although in our experiments we used a simple first-price auction, our algorithms are compatible with strictly incentive-compatible auctions and pricing mechanisms. We have analyzed the performance of our algorithms in two different scenarios: assuming a static intrinsic click-through rate associated to each ad and in the more general case in which those rates may vary dynamically with time. Our main result is an algorithm that performs reasonably well in terms of revenue as the traditionally used, while notably increasing the diversification. In some scenarios, our newly introduced algorithms even outperform the traditional ones. © 2007 IEEE. Fil:Heiber, P.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_07695300_v_n_p22_Feuerstein
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Commerce Image retrieval Click-through rates Price auctions Pricing mechanisms Stochastic algorithms Economics
spellingShingle	Commerce Image retrieval Click-through rates Price auctions Pricing mechanisms Stochastic algorithms Economics Feuerstein, E. Martínez-Viademonte, J. Heiber, P.A. Baeza-Yates, R. New stochastic algorithms for scheduling ads in sponsored search
topic_facet	Commerce Image retrieval Click-through rates Price auctions Pricing mechanisms Stochastic algorithms Economics
description	We introduce a family of algorithms for the selection of ads in sponsored search that intends to increase the variety of choices, while not significantly reducing revenue and maintaining an incentive for advertisers to keep their bids as high as possible. Diversification of ads may be convenient for many reasons, which we also expose. Our algorithms try to distribute the available slots among all ads, using a proportional mechanism based on the bids and the expected click-through rates of the ads. Although in our experiments we used a simple first-price auction, our algorithms are compatible with strictly incentive-compatible auctions and pricing mechanisms. We have analyzed the performance of our algorithms in two different scenarios: assuming a static intrinsic click-through rate associated to each ad and in the more general case in which those rates may vary dynamically with time. Our main result is an algorithm that performs reasonably well in terms of revenue as the traditionally used, while notably increasing the diversification. In some scenarios, our newly introduced algorithms even outperform the traditional ones. © 2007 IEEE.
format	CONF
author	Feuerstein, E. Martínez-Viademonte, J. Heiber, P.A. Baeza-Yates, R.
author_facet	Feuerstein, E. Martínez-Viademonte, J. Heiber, P.A. Baeza-Yates, R.
author_sort	Feuerstein, E.
title	New stochastic algorithms for scheduling ads in sponsored search
title_short	New stochastic algorithms for scheduling ads in sponsored search
title_full	New stochastic algorithms for scheduling ads in sponsored search
title_fullStr	New stochastic algorithms for scheduling ads in sponsored search
title_full_unstemmed	New stochastic algorithms for scheduling ads in sponsored search
title_sort	new stochastic algorithms for scheduling ads in sponsored search
url	http://hdl.handle.net/20.500.12110/paper_07695300_v_n_p22_Feuerstein
work_keys_str_mv	AT feuersteine newstochasticalgorithmsforschedulingadsinsponsoredsearch AT martinezviademontej newstochasticalgorithmsforschedulingadsinsponsoredsearch AT heiberpa newstochasticalgorithmsforschedulingadsinsponsoredsearch AT baezayatesr newstochasticalgorithmsforschedulingadsinsponsoredsearch
_version_	1807321930733191168

New stochastic algorithms for scheduling ads in sponsored search

Ejemplares similares