A Keyword Extraction Based Model for Web Advertisement

  • Ning Zhou
  • Jiaxin Wu
  • Shaolong Zhang
Conference paper
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 252)


In this paper, a keyword extraction based model is proposed to deal with web advertisement. In our model, we take web advertisement as an information retrieval problem. Web page and advertisement are firstly represented with a simple data structure which will be the source file for keyword extraction based on x2-measure for single document. Later we get two vectors to make a retrieval process with a specific similarity function. This model is suitable for common cases of web advertisement. It supports the web page selection in view of advertisement as well as the advertisement selection for specific web page.


Vector Space Model Word Segmentation Text Field Banner Advertisement Keyword Extraction 


  1. 1.
    Matsuo Y, Ishizuka M. “Keyword extraction from a single document using word co-occurrence statistical information”. Int’l Journal on Artificial Intelligence Tools, 2004, 13(1):157–169CrossRefGoogle Scholar
  2. 2.
    Ricardo Baeza-Yates, et al. mordern information retrieval. 1999, ACM press.Google Scholar
  3. 3.
    Ng V, Kwan-Ho Mok. An intelligent agent for Web advertisements. Cooperative Database Systems for Advanced Applications, 23–24 April 2001 Pages:102–109Google Scholar
  4. 4.
    Amiri A, Menon S. Scheduling web banner advertisements with multiple display frequencies Systems, Man and Cybernetics, Part A, IEEE Transactions on Volume 36, Issue 2, March 2006 Pages:245–251Google Scholar
  5. 5.
    Thawani A, Gopalan S. “Event driven semantics based ad selection”. Multimedia and Expo, 2004. ICME’ 04,27–30 June 2004 Pages: 1875–1878Google Scholar
  6. 6.
    Salton, G., Buckley, C, “Term weighting approaches in automatic text retrieval.” Information Processing and Management, 1988. 24(5):513–523.CrossRefGoogle Scholar
  7. 7.
    Google AdWards, http://www.google.com/intl/zh-CN/ads/. access date: December 21, 2006

Copyright information

© IFIP International Federation for Information Processing 2007

Authors and Affiliations

  • Ning Zhou
    • 1
  • Jiaxin Wu
    • 1
    • 2
  • Shaolong Zhang
    • 2
  1. 1.Research Center of Information ResourcesWuhan UniversityWuhanChina
  2. 2.School of Information ManagementWuhan UniversityWuhanChina

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