Finding advertising keywords on web pages

  • Authors:
  • Wen-tau Yih;Joshua Goodman;Vitor R. Carvalho

  • Affiliations:
  • Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • Proceedings of the 15th international conference on World Wide Web
  • Year:
  • 2006

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Abstract

A large and growing number of web pages display contextual advertising based on keywords automatically extracted from the text of the page, and this is a substantial source of revenue supporting the web today. Despite the importance of this area, little formal, published research exists. We describe a system that learns how to extract keywords from web pages for advertisement targeting. The system uses a number of features, such as term frequency of each potential keyword, inverse document frequency, presence in meta-data, and how often the term occurs in search query logs. The system is trained with a set of example pages that have been hand-labeled with "relevant" keywords. Based on this training, it can then extract new keywords from previously unseen pages. Accuracy is substantially better than several baseline systems.