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

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. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval--search process; H.2.8 [Database Management]: Database Applications--data mining General Terms Algorithms, Experimentation, Measurement, Performance

• Type: Conference
• Year: 2008
• Where: CIKM
• Authors: Xuerui Wang, Andrei Z. Broder, Marcus Fontoura, Vanja Josifovski
• Keywords: CIKM 2008, Contextual Advertising, Enormous Computational Task, Information Management, Two-level Search Process