Predicting web site audience demographics for web advertising targeting using multi-web site clickstream data
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Other versions of this item:
- K.W. de Bock & D. van den Poel, 2010. "Predicting website audience demographics for web advertising targeting using multi website clickstream data," Post-Print hal-00800168, HAL.
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Cited by:
- D. Thorleuchter & D. Van Den Poel & A. Prinzie, 2011. "Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/733, Ghent University, Faculty of Economics and Business Administration.
- DE CNUDDE, Sofie & MARTENS, David & EVGENIOU, Theodoros & PROVOST, Foster, 2017. "A benchmarking study of classification techniques for behavioral data," Working Papers 2017005, University of Antwerp, Faculty of Business and Economics.
- Moritz Zahn & Stefan Feuerriegel & Niklas Kuehl, 2022. "The Cost of Fairness in AI: Evidence from E-Commerce," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 335-348, June.
- Yaxi Liu & Dayu Cheng & Tao Pei & Hua Shu & Xianhui Ge & Ting Ma & Yunyan Du & Yang Ou & Meng Wang & Lianming Xu, 2020. "Inferring gender and age of customers in shopping malls via indoor positioning data," Environment and Planning B, , vol. 47(9), pages 1672-1689, November.
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Keywords
demography prediction; demographic targeting; web advertising; Random Forests; web user profiling; clickstream analysis;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-FOR-2009-12-19 (Forecasting)
- NEP-ICT-2009-12-19 (Information and Communication Technologies)
- NEP-MKT-2009-12-19 (Marketing)
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