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Born to trade: a genetically evolved keyword bidder for sponsored search

Michael Munsey, Jonathan Veilleux, Sindhura Bikkani, Ankur Teredesai and Martine De Cock UGent (2010) IEEE Congress on Evolutionary Computation.
abstract
In sponsored search auctions, advertisers choose a set of keywords based on products they wish to market. They bid for advertising slots that will be displayed on the search results page when a user submits a query containing the keywords that the advertiser selected. Deciding how much to bid is a real challenge: if the bid is too low with respect to the bids of other advertisers, the ad might not get displayed in a favorable position; a bid that is too high on the other hand might not be profitable either, since the attracted number of conversions might not be enough to compensate for the high cost per click. In this paper we propose a genetically evolved keyword bidding strategy that decides how much to bid for each query based on historical data such as the position obtained on the previous day. In light of the fact that our approach does not implement any particular expert knowledge on keyword auctions, it did remarkably well in the Trading Agent Competition at IJCAI2009.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
in
IEEE Congress on Evolutionary Computation
issue title
2010 IEEE congress on evolutionary computation (CEC)
pages
8 pages
publisher
IEEE
place of publication
New York, NY, USA
conference name
2010 IEEE World congress on Computational Intelligence (WCCI 2010)
conference location
Barcelona, Spain
conference start
2010-07-18
conference end
2010-07-23
Web of Science type
Proceedings Paper
Web of Science id
000287375800051
ISBN
9781424481262
DOI
10.1109/CEC.2010.5585963
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1108124
handle
http://hdl.handle.net/1854/LU-1108124
date created
2011-01-21 14:43:37
date last changed
2017-03-30 14:08:02
@inproceedings{1108124,
  abstract     = {In sponsored search auctions, advertisers choose a set of keywords based on products they wish to market. They bid for advertising slots that will be displayed on the search results page when a user submits a query containing the keywords that the advertiser selected. Deciding how much to bid is a real challenge: if the bid is too low with respect to the bids of other advertisers, the ad might not get displayed in a favorable position; a bid that is too high on the other hand might not be profitable either, since the attracted number of conversions might not be enough to compensate for the high cost per click.
In this paper we propose a genetically evolved keyword bidding strategy that decides how much to bid for each query based on historical data such as the position obtained on the previous day. In light of the fact that our approach does not implement any particular expert knowledge on keyword auctions, it did remarkably well in the Trading Agent Competition at IJCAI2009.},
  author       = {Munsey, Michael and Veilleux, Jonathan and Bikkani, Sindhura and Teredesai, Ankur and De Cock, Martine},
  booktitle    = {IEEE Congress on Evolutionary Computation},
  isbn         = {9781424481262},
  language     = {eng},
  location     = {Barcelona, Spain},
  pages        = {8},
  publisher    = {IEEE},
  title        = {Born to trade: a genetically evolved keyword bidder for sponsored search},
  url          = {http://dx.doi.org/10.1109/CEC.2010.5585963},
  year         = {2010},
}

Chicago
Munsey, Michael, Jonathan Veilleux, Sindhura Bikkani, Ankur Teredesai, and Martine De Cock. 2010. “Born to Trade: a Genetically Evolved Keyword Bidder for Sponsored Search.” In IEEE Congress on Evolutionary Computation. New York, NY, USA: IEEE.
APA
Munsey, M., Veilleux, J., Bikkani, S., Teredesai, A., & De Cock, M. (2010). Born to trade: a genetically evolved keyword bidder for sponsored search. IEEE Congress on Evolutionary Computation. Presented at the 2010 IEEE World congress on Computational Intelligence (WCCI 2010), New York, NY, USA: IEEE.
Vancouver
1.
Munsey M, Veilleux J, Bikkani S, Teredesai A, De Cock M. Born to trade: a genetically evolved keyword bidder for sponsored search. IEEE Congress on Evolutionary Computation. New York, NY, USA: IEEE; 2010.
MLA
Munsey, Michael, Jonathan Veilleux, Sindhura Bikkani, et al. “Born to Trade: a Genetically Evolved Keyword Bidder for Sponsored Search.” IEEE Congress on Evolutionary Computation. New York, NY, USA: IEEE, 2010. Print.