Journal of Guangdong University of Technology ›› 2018, Vol. 35 ›› Issue (03): 54-60.doi: 10.12052/gdutxb.170144

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Bidding Prediction of Advertisement Keywords via Group Role Combination

Liu Dong-ning1, Wu Xiao-liang1, Lu Ming-jian2, Lu Ming-jun1   

  1. 1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China;
    2. College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
  • Received:2017-10-31 Online:2018-05-09 Published:2018-04-26

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Abstract: With respect to the cost of advertising investment being limited, the processing of rationalizing and maximizing marketing investment via online keyword bidding is hard. In order to solve this problem, an optimization method is proposed, which is based on Role-Based Collaboration (RBC) and its E-CARGO model. According to history data, it models the problem by mapping keywords and their combinations to roles and groups (Group Role Combination) and using linear programming to obtain the best investment prediction. The proposed methods are verified by simulation experiments. The experimental results present the practicability of the proposed solutions. Using the proposed methods, decision makers need only to provide investment budget. The maximal profitability, the rate of return and the investment range are obtained.

Key words: portfolio, advertising keywords, role-based collaboration, E-CARGO, linear programming

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