关键词: 用户模拟器, 交互式检索, 强化学习, 人工智能, 用户个性化特征

Abstract:

With the development of retrieval technology, interactive retrieval becomes more and more important in the field of information retrieval. Interactive retrieval adds the ability to capture the fine-grained behavior of users in the traditional retrieval mode in order to improve the performance of the retrieval engine through the user simulator. Rule-based user simulators lack of personalized user features and cannot learn new behavior, poor adaptability. Model-based user simulators can learn more user personalized behavior characteristics, which can effectively improve the performance of interactive search engine. This paper describes the interactive process of user simulator and retrieval engine, summarizes the construction methods of rule-based user simulator and model-based user simulator and the evaluation methods of user simulator in recent years, and focuses on the introduction of model-based user simulator. Finally, the paper compares the differences between the user simulator for interactive retrieval and the traditional user simulator, and takes the interactive dissertation retrieval scenario as an example to forecast the application of the user simulator.

Key words: user simulator, interactive retrieval, reinforcement learning, artificial intelligence, personalized characteristics of users