图 书 馆
搜索广告中通过生成对抗网络的罕见查询扩展Rare Query Expansion Through Generative Adversarial Networks in Search Advertising |
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| 课程网址: | http://videolectures.net/kdd2018_lee_search_advertising/ |
| 主讲教师: | Mu-Chu Lee |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Generative Adversarial Networks (GAN) have achieved great success in generating realistic synthetic data like images, tags, and sentences. We explore using GAN to generate bid keywords directly from query in sponsored search ads selection, especially for rare queries. Specifically, in the query expansion (query-keyword matching) scenario in search advertising, we train a sequence to sequence model as the generator to generate keywords, conditioned on the user query, and use a recurrent neural network model as the discriminator to play an adversarial game with the generator. By applying the trained generator, we can generate keywords directly from a given query, so that we can highly improve the effectiveness and efficiency of query-keyword matching based ads selection in search advertising. We trained the proposed model in the clicked query-keyword pair dataset from a commercial search advertising system. Evaluation results show that the generated keywords are more relevant to the given query compared with the baseline model and they have big potential to bring extra revenue improvement. |
| 关 键 词: | 生成对抗网络; 赞助搜索广告选择; 点击查询关键字; 商业搜索广告系统 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-01-28：cyh |
| 最后编审: | 2023-01-28：cyh |
| 阅读次数: | 23 |