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    Batch-mode computational advertising based on modern portfolio theory

    Zhang, Dell and Lu, J. (2009) Batch-mode computational advertising based on modern portfolio theory. In: Azzopardi, L. and Kazai, G. and Robertson, S.E. and Ruger, S.M. and Shokouhi, M. and Song, D. and Yilmaz, E. (eds.) Advances in Information Retrieval Theory. Lecture Notes In Computer Science 386 5766. Berlin, Germany: Springer, pp. 380-383. ISBN 9783642044168.

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    The research on computational advertising so far has focused on finding the single best ad. However, in many real situations, more than one ad can be presented. Although it is possible to address this problem myopically by using a single-ad optimisation technique in serial-mode, i.e., one at a time, this approach can be ineffective and inefficient because it ignores the correlation between ads. In this paper, we make a leap forward to address the problem of finding the best ads in batch-mode, i.e., assembling the optimal set of ads to be presented altogether. The key idea is to achieve maximum revenue while controlling the level of risk by diversifying the set of ads. We show how the Modern Portfolio Theory can be applied to this problem to provide elegant solutions and deep insights.


    Item Type: Book Section
    Additional Information: Second International Conference on the Theory of Information Retrieval, ICTIR 2009 Cambridge, UK, September 10-12, 2009 Proceedings
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Administrator
    Date Deposited: 30 May 2013 09:27
    Last Modified: 09 Aug 2023 12:33


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