广东工业大学学报 ›› 2018, Vol. 35 ›› Issue (03): 54-60.doi: 10.12052/gdutxb.170144

• 综合研究 • 上一篇    下一篇

广告关键字群组角色组合投资预测研究

刘冬宁1, 武小亮1, 卢明健2, 卢明俊1   

  1. 1. 广东工业大学 计算机学院, 广东 广州 510006;
    2. 深圳大学 土木工程学院, 广东 深圳 518060
  • 收稿日期:2017-10-31 出版日期:2018-05-09 发布日期:2018-04-26
  • 作者简介:刘冬宁(1979-),男,副教授,博士,主要研究方向为协同计算、人工智能逻辑.E-mail:liudn@gdut.edu.cn
  • 基金资助:
    国家自然科学基金资助项目（61402118）；广东省科技计划项目（2016B010108007）；广州市科技计划项目（201604020145）；广州市天河区科技计划项目（201602YH029）

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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摘要： 为解决广告投入成本受限时通过在线关键词投资与组合使营销利润最大化及投资合理化问题，以“基于角色的协同”工程方法及其E-CARGO模型对淘宝商家的广告关键词投资问题进行建模，结合历史数据，采用群组角色组合线性规划方法对广告关键词投资做效益计算，以获得周期性历史数据预测与支持下的广告关键字最佳投资方案.通过实验仿真论证，该方法高效、可靠，能使投资者在投资费用受限情况下尽可能利润最大化，并对投资回报率问题与投资区间进行了分析，经过定量计算与定性分析给出理性投资建议.

关键词: 投资组合, 广告关键词, 基于角色的协同, E-CARGO, 线性规划

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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