Keyword Optimization in Sponsored Search via Feature Selection

Svetlana Kiritchenko, Mikhail Jiline
Proceedings of the Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery at ECML/PKDD 2008, PMLR 4:122-134, 2008.

Abstract

Sponsored search is a new application domain for the feature selection area of research. When a user searches for products or services using the Internet, most of the major search engines would return two sets of results: regular web pages and paid advertisements. An advertising company provides a set of keywords associated with an ad. If one of these keywords is present in a user’s query, the ad is displayed, but the company is charged only if the user actually clicks on the ad. Ultimately, a company would like to advertise on the most effective keywords to attract only prospective customers. A set of keywords can be optimized based on historic performance. We propose to optimize advertising keywords with feature selection techniques applied to the set of all possible word combinations comprising past users’ queries. Unlike previous work in this area, our approach not only recognizes the most profitable keywords, but also discovers more specific combinations of keywords and other relevant words.

Cite this Paper

BibTeX
@InProceedings{pmlr-v4-kiritchenko08a, title = {Keyword Optimization in Sponsored Search via Feature Selection}, author = {Kiritchenko, Svetlana and Jiline, Mikhail}, booktitle = {Proceedings of the Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery at ECML/PKDD 2008}, pages = {122--134}, year = {2008}, editor = {Saeys, Yvan and Liu, Huan and Inza, Iñaki and Wehenkel, Louis and Pee, Yves Van de}, volume = {4}, series = {Proceedings of Machine Learning Research}, address = {Antwerp, Belgium}, month = {15 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v4/kiritchenko08a/kiritchenko08a.pdf}, url = {https://proceedings.mlr.press/v4/kiritchenko08a.html}, abstract = {Sponsored search is a new application domain for the feature selection area of research. When a user searches for products or services using the Internet, most of the major search engines would return two sets of results: regular web pages and paid advertisements. An advertising company provides a set of keywords associated with an ad. If one of these keywords is present in a user’s query, the ad is displayed, but the company is charged only if the user actually clicks on the ad. Ultimately, a company would like to advertise on the most effective keywords to attract only prospective customers. A set of keywords can be optimized based on historic performance. We propose to optimize advertising keywords with feature selection techniques applied to the set of all possible word combinations comprising past users’ queries. Unlike previous work in this area, our approach not only recognizes the most profitable keywords, but also discovers more specific combinations of keywords and other relevant words.} }
Endnote
%0 Conference Paper %T Keyword Optimization in Sponsored Search via Feature Selection %A Svetlana Kiritchenko %A Mikhail Jiline %B Proceedings of the Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery at ECML/PKDD 2008 %C Proceedings of Machine Learning Research %D 2008 %E Yvan Saeys %E Huan Liu %E Iñaki Inza %E Louis Wehenkel %E Yves Van de Pee %F pmlr-v4-kiritchenko08a %I PMLR %P 122--134 %U https://proceedings.mlr.press/v4/kiritchenko08a.html %V 4 %X Sponsored search is a new application domain for the feature selection area of research. When a user searches for products or services using the Internet, most of the major search engines would return two sets of results: regular web pages and paid advertisements. An advertising company provides a set of keywords associated with an ad. If one of these keywords is present in a user’s query, the ad is displayed, but the company is charged only if the user actually clicks on the ad. Ultimately, a company would like to advertise on the most effective keywords to attract only prospective customers. A set of keywords can be optimized based on historic performance. We propose to optimize advertising keywords with feature selection techniques applied to the set of all possible word combinations comprising past users’ queries. Unlike previous work in this area, our approach not only recognizes the most profitable keywords, but also discovers more specific combinations of keywords and other relevant words.
RIS
TY - CPAPER TI - Keyword Optimization in Sponsored Search via Feature Selection AU - Svetlana Kiritchenko AU - Mikhail Jiline BT - Proceedings of the Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery at ECML/PKDD 2008 DA - 2008/09/11 ED - Yvan Saeys ED - Huan Liu ED - Iñaki Inza ED - Louis Wehenkel ED - Yves Van de Pee ID - pmlr-v4-kiritchenko08a PB - PMLR DP - Proceedings of Machine Learning Research VL - 4 SP - 122 EP - 134 L1 - http://proceedings.mlr.press/v4/kiritchenko08a/kiritchenko08a.pdf UR - https://proceedings.mlr.press/v4/kiritchenko08a.html AB - Sponsored search is a new application domain for the feature selection area of research. When a user searches for products or services using the Internet, most of the major search engines would return two sets of results: regular web pages and paid advertisements. An advertising company provides a set of keywords associated with an ad. If one of these keywords is present in a user’s query, the ad is displayed, but the company is charged only if the user actually clicks on the ad. Ultimately, a company would like to advertise on the most effective keywords to attract only prospective customers. A set of keywords can be optimized based on historic performance. We propose to optimize advertising keywords with feature selection techniques applied to the set of all possible word combinations comprising past users’ queries. Unlike previous work in this area, our approach not only recognizes the most profitable keywords, but also discovers more specific combinations of keywords and other relevant words. ER -
APA
Kiritchenko, S. & Jiline, M.. (2008). Keyword Optimization in Sponsored Search via Feature Selection. Proceedings of the Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery at ECML/PKDD 2008, in Proceedings of Machine Learning Research 4:122-134 Available from https://proceedings.mlr.press/v4/kiritchenko08a.html.

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