Abstract
Pay-per-click advertising is one of the most paved ways of online advertising today. However the top ranking keywords are extremely costly. Since search terms have a “long tail” behaviour, they may be used for a more cost-effective way of selecting the right keywords, achieving similar traffic, and reducing the cost considerably. This paper proposes a methodology that, exploiting linguistic knowledge, identifies cost effective bid keyword in the long tail distribution. The experiments show that these keywords are highly relevant (90% average precision) and better targeted than those suggested by other methods, while enabling reduced cost of an ad campaign.
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D’Avanzo, E., Kuflik, T., Elia, A. (2011). Online Advertising Using Linguistic Knowledge. In: D'Atri, A., Ferrara, M., George, J., Spagnoletti, P. (eds) Information Technology and Innovation Trends in Organizations. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2632-6_17
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DOI: https://doi.org/10.1007/978-3-7908-2632-6_17
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