文章基于用户视角揭示了科研人员的个性化推荐需求，构建了个性化推荐需求层次模型。丰富了用户视角下个性化推荐研究，为知识服务平台更具针对性地设计个性化推荐提供了理论指导，为实现个性化推荐算法与用户视角下个性化推荐研究的融合提供了参考。研究采用半结构化深度访谈，对22名科研人员进行了访谈，使用NVivo11质性分析工具进行数据分析。研究发现，科研人员的个性化推荐需求包括内容需求、交互功能需求、界面布局需求、效能需求和情感需求，其中，需要首先满足的是内容需求，其次是交互功能需求和界面布局需求，再次是效能需求，最后是情感需求。基于此，研究提出科研人员个性化推荐需求层次模型。此外，研究表明，任务、交互检索习惯、推荐解释影响着科研人员对个性化推荐的需求和关注。

This study aims to explore the personalized recommendation needs (PRNs) of researchers from user's perspective.  Semi-structured in-depth interviews with 22 researchers were conducted, and NVivo11 was used for data analysis. Five PRNs were identified: content needs, interactive functional needs, interface layout needs, effectiveness needs and emotional needs. Furthermore, the PRNs hierarchical model indicates that content needs are basic needs, should be satisfied firstly, interactive functional needs, interface layout needs should be satisfied secondly, followed by effectiveness needs and emotional needs. In addition, tasks, interactive retrieval habits, and recommendation interpretation affect the PRNs of researchers. Based on the results, a PRNs hierarchical model is developed. This study has implications for incorporating personalized recommendation needs into algorithms. It adds new knowledge about personalized recommendation to the research community and informs personalized recommendation system design.