Dynamic Budget Adjustment in Search Auctions
文献类型：会议论文
| 作者 | Zhang, Jie ; Yang, Yanwu; Qin, Rui; Zeng, Daniel; Li, Xin
|
| 出版日期 | 2011-12-03 |
| 会议日期 | Dec. 3-4, 2011 |
| 会议地点 | Shanghai, China |
| 关键词 | Search Auctions Budget Adjustment Reinforcement Learning Dynamical Adjustment |
| 英文摘要 | With serious advertising budget constraints, advertisers have to adjust their daily budget according to the performance of advertisements in real time. Thus we can leave precious budgets to better opportunities in the future, and avoid the surge of ineffective clicks for unnecessary costs. However, advertisers usually have no sufficient knowledge and time for real-time advertising operations in search auctions. We formulate the budget adjustment problem as a state-action decision process in the reinforcement learning (RL) framework. Considering dynamics of marketing environments and some distinctive features of search auctions, we extend continuous reinforcement learning to fit the budget decision scenarios. The market utility is defined as discounted total clicks to get during the remaining period of an advertising schedule. We conduct experiments to validate and evaluate our strategy of budget adjustment with real world data from search advertising campaigns. Experimental results showed that our strategy outperforms the two other baseline strategies. |
| 会议录 | Proceedings of the 21th Workshop on Information Technologies and Systems
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19637]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 作者单位 | The State Key Lab of Intelligent Control and Management of Complex Systems, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Zhang, Jie,Yang, Yanwu,Qin, Rui,et al. Dynamic Budget Adjustment in Search Auctions[C]. 见:. Shanghai, China. Dec. 3-4, 2011. |
入库方式： OAI收割
来源：自动化研究所
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