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Refereed Papers
Track: Data Mining: Log Analysis
Paper Title:
Using the Wisdom of the Crowds for Keyword Generation
Authors:
- Ariel Fuxman(Microsoft Research)
- Panayiotis Tsaparas(Microsoft Research)
- Kannan Achan(Microsoft Research)
- Rakesh Agrawal(Microsoft Research)
Abstract:
In the sponsored search model, search engines are paid by businesses that are
interested in displaying ads for their site alongside the search results.
Businesses bid for keywords, and their ad is displayed when the
keyword is queried to the search engine. An important problem in this process
is emph{keyword generation}: given a business that is interested in launching
a campaign, suggest keywords that are related to that campaign. We address this
problem by making use of the query logs of the search engine. We identify
queries related to a campaign by exploiting the associations between queries
and URLs as they are captured by the user's clicks. These queries form good
keyword suggestions since they capture the ``wisdom of the crowd'' as to what
is related to a site. We formulate the problem as a semi-supervised learning
problem, and propose algorithms within the Markov Random Field model. We
perform experiments with real query logs, and we demonstrate that our
algorithms scale to large query logs and produce meaningful results.
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