图 书 馆
问答：互动推荐的两阶段方法Q&R: A Two‑Stage Approach toward Interactive Recommendation |
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| 课程网址: | http://videolectures.net/kdd2018_beutel_interactive_recommendatio... |
| 主讲教师: | Alex Beutel |
| 开课单位: | 谷歌股份有限公司的研究 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Recommendation systems, prevalent in many applications, aim to surface to users the right content at the right time. Recently, researchers have aspired to develop conversational systems that offer seamless interactions with users, more effectively eliciting user preferences and offering better recommendations. Taking a step towards this goal, this paper explores the two stages of a single round of conversation with a user: which question to ask the user, and how to use their feedback to respond with a more accurate recommendation. Following these two stages, first, we detail an RNN-based model for generating topics a user might be interested in, and then extend a state-of-the-art RNN-based video recommender to incorporate the user’s selected topic. We describe our proposed system Q&R, i.e., Question & Recommendation, and the surrogate tasks we utilize to bootstrap data for training our models. We evaluate different components of Q&R on live traffic in various applications within YouTube: User Onboarding, Homepage Recommendation, and Notifications. Our results demonstrate that our approach improves upon state-of-the-art recommendation models, including RNNs, and makes these applications more useful, such as a >1% increase in video notifications opened. Further, our design choices can be useful to practitioners wanting to transition to more conversational recommendation systems. |
| 关 键 词: | 互动推荐; 两阶段方法; 流行的推荐系统; 激发用户偏好; 训练模型的代理任务 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-03-27：cyh |
| 最后编审: | 2023-03-27：cyh |
| 阅读次数: | 19 |