A note on search based forecasting of ad volume in contextual advertising

ABSTRACT

In contextual advertising, estimating the number of impressions of an ad is critical in planning and budgeting advertising campaigns. However, producing this forecast, even within large margins of error, is quite challenging. We attack this problem by simulating the presence of a given ad with its associated bid over historical data, involving billions of impressions. This apparently enormous computational task is reduced to a search task involving only the set of distinct pages in the data. Furthermore the search is made more efficient using a two-level search process. Experimental results show that our approach can accurately forecast the expected number of impressions of contextual ads in real time.

REFERENCES

• 1: Andrei Z. Broder , David Carmel , Michael Herscovici , Aya Soffer , Jason Zien, Efficient query evaluation using a two-level retrieval process, Proceedings of the twelfth international conference on Information and knowledge management, November 03-08, 2003, New Orleans, LA, USA [doi>10.1145/956863.956944]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Search process

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

General Terms:
Algorithms, Experimentation, Measurement, Performance

Keywords:
content match, contextual advertising, impression forecasting, internet monetization, online advertising, wand