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Issue No.02 - April-June (2013 vol.6)
pp: 168-176
Yanwu Yang , Chinese Academy of Sciences, Beijing
Jie Zhang , Chinese Academy of Sciences, Beijing
Rui Qin , Chinese Academy of Sciences, Beijing
Juanjuan Li , Chinese Academy of Sciences, Beijing
Baiyu Liu , University of Science and Technology Beijing, Beijing
Zhong Liu , National University of Defense Technology, Hunan
How to rationally allocate the limited advertising budget is a critical issue in sponsored search auctions. There are plenty of uncertainties in the mapping from the budget into the advertising performance. This paper presented some preliminary efforts to deal with uncertainties in search marketing environments, following principles of a hierarchical budget optimization framework (BOF). We proposed a stochastic, risk-constrained budget strategy, by considering a random factor of clicks per unit cost to capture a kind of uncertainty at the campaign level. Uncertainties of random factors at the campaign level lead to risk at the market/system level. We also proved its theoretical soundness through analyzing some desirable properties. Some computational experiments were made to evaluate our proposed budget strategy with real-word data collected from reports and logs of search advertising campaigns. Experimental results illustrated that our strategy outperforms two baseline strategies. We also noticed that 1) the risk tolerance has great influences on the determination of optimal budget solutions; 2) the higher risk tolerance leads to more expected revenues.
Advertising, Optimization, Uncertainty, Stochastic processes, Resource management, Search problems, Portals, search auctions, Budget optimization, budget decisions, optimal strategy, stochastic strategy
Yanwu Yang, Jie Zhang, Rui Qin, Juanjuan Li, Baiyu Liu, Zhong Liu, "Budget Strategy in Uncertain Environments of Search Auctions: A Preliminary Investigation", IEEE Transactions on Services Computing, vol.6, no. 2, pp. 168-176, April-June 2013, doi:10.1109/TSC.2011.60
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