Deep Reinforcement Learning for Personalized Search Story Recommendation
Jason, null, Zhang, null, Yin, Junming, Lee, Dongwon, Zhu, Linhong
ABSTRACT In recent years, search story, a combined display with other organic channels, has become a major source of user traffic on platforms such as e-commerce search platforms, news feed platforms and web and image search platforms. The recommended search story guides a user to identify her own preference and personal intent, which subsequently influences the user's real-time and long-term search behavior. As search stories become increasingly important, in this work, we study the problem of personalized search story recommendation within a search engine, which aims to suggest a search story relevant to both a search keyword and an individual user's interest. To address the challenge of modeling both immediate and future values of recommended search stories (i.e., cross-channel effect), for which conventional supervised learning framework is not applicable, we resort to a Markov decision process and propose a deep reinforcement learning architecture trained by both imitation learning and reinforcement learning. We empirically demonstrate the effectiveness of our proposed approach through extensive experiments on real-world data sets from JD.com. 1. INTRODUCTION Imagine that a customer visits a retail shop to purchase a dress which is to her liking. As the customer walks in, a business assistant is present to assist the customer by answering questions on fashion trend or suggesting related dresses. In online e-commerce applications, more business units are adding a component that plays a similar role as the business assistant in a shop. In this paper, we are interested in a particular component, commonly known as search story, that has become popular among e-commerce search engines on many online platforms. For instance, in news feed platforms and web and image search platforms, each search story is a display of recommended high-quality content which is relevant to a user's personal interests. In e-commerce search (a) Display search story within organic product item search page (b) Landing page after clicking search story, which contains both shopping guides and shopping product items Figure 1: An illustrated (not a screenshot) example of search story recommendation.
Jul-26-2019
- Genre:
- Research Report > Experimental Study (0.67)
- Industry:
- Information Technology > Services (1.00)
- Marketing (0.93)
- Technology: