Keyword Optimization in Sponsored Search via Feature Selection
Svetlana Kiritchenko, Mikhail Jiline;
JMLR W&P 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.
