Keyword generation for search engine advertising using semantic similarity between terms

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Keyword generation for search engine advertising using semantic similarity between terms

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ACM International Conference Proceeding Series; Vol. 258 archive
Proceedings of the ninth international conference on Electronic commerce table of contents

Minneapolis, MN, USA

SESSION: Session M4: sponsored search on the internet I table of contents

Pages: 89 - 94

Year of Publication: 2007

ISBN:978-1-59593-700-1

Authors

Vibhanshu Abhishek	The Wharton School, Philadelphia, PA
Kartik Hosanagar	The Wharton School, Philadelphia, PA

Sponsors

SIGART: ACM Special Interest Group on Artificial Intelligence
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 25, Downloads (12 Months): 274, Citation Count: 5

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ABSTRACT

An important problem in search engine advertising is key-word¹ generation. In the past, advertisers have preferred to bid for keywords that tend to have high search volumes and hence are more expensive. An alternate strategy involves bidding for several related but low volume, inexpensive terms that generate the same amount of traffic cumulatively but are much cheaper. This paper seeks to establish a mathematical formulation of this problem and suggests a method for generation of several terms from a seed keyword. This approach uses a web based kernel function to establish semantic similarity between terms. The similarity graph is then traversed to generate keywords that are related but cheaper.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY 5

	Ariel Fuxman , Panayiotis Tsaparas , Kannan Achan , Rakesh Agrawal, Using the wisdom of the crowds for keyword generation, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China
	Hao Wu , Guang Qiu , Xiaofei He , Yuan Shi , Mingcheng Qu , Jing Shen , Jiajun Bu , Chun Chen, Advertising keyword generation using active learning, Proceedings of the 18th international conference on World wide web, April 20-24, 2009, Madrid, Spain
	William Chang , Patrick Pantel , Ana-Maria Popescu , Evgeniy Gabrilovich, Towards intent-driven bidterm suggestion, Proceedings of the 18th international conference on World wide web, April 20-24, 2009, Madrid, Spain
	Luís Sarmento , Paulo Trezentos , João Pedro Gonçalves , Eugénio Oliveira, Inferring local synonyms for improving keyword suggestion in an on-line advertisement system, Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising, p.37-45, June 28-28, 2009, Paris, France
	Anton Schwaighofer , Joaquin Quiñonero Candela , Thomas Borchert , Thore Graepel , Ralf Herbrich, Scalable clustering and keyword suggestion for online advertisements, Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising, p.27-36, June 28-28, 2009, Paris, France