图 书 馆
基于性能的情境广告系统的开发与探索Exploitation and Exploration in a Performance based Contextual Advertising System |
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| 课程网址: | http://videolectures.net/kdd2010_zhang_eepb/ |
| 主讲教师: | Ruofei Zhang |
| 开课单位: | 雅虎公司 |
| 开课时间: | 2010-10-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of online data inevitably makes an advertising system choose between maximizing its expected revenue according to its current knowledge in short term (exploitation) and trying to learn more about the unknown to improve its knowledge (exploration), since the latter might increase its revenue in the future. The exploitation and exploration (EE) tradeoff has been extensively studied in the reinforcement learning community, however, not been paid much attention in online advertising until recently. In this paper, we develop two novel EE strategies for online advertising. Specifically, our methods can adaptively balance the two aspects of EE by automatically learning the optimal tradeoff and incorporating confidence metrics of historical performance. Within a deliberately designed offline simulation framework we apply our algorithms to an industry leading performance based contextual advertising system and conduct extensive evaluations with real online event log data. The experimental results and detailed analysis reveal several important findings of EE behaviors in online advertising and demonstrate that our algorithms perform superiorly in terms of ad reach and click-through-rate (CTR). |
| 关 键 词: | 在线广告; 排名系统; 流媒体 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-03-25：chenxin |
| 阅读次数: | 90 |