用控制理论建模长期目标推荐系统，让推荐更智能。
Trajectory-Based Recommender Systems as Control Systems
- 将推荐系统视为控制过程，以轨迹为核心设计框架。
- 教育推荐系统可被统一纳入该理论体系，提升长期效果。
- 为长期目标型推荐提供新范式，适合教育、职业规划场景。
推荐系统（RS）是关键研究领域，在信息过载时代愈发重要。本文探讨轨迹型推荐系统（TBRS），这类系统虽已有诸多研究，却缺乏统一框架。我们提出控制理论可作为形式化和解决TBRS问题的合适基础。TBRS，又称长期目标推荐系统，与经典推荐系统共享核心原则，但其核心在于‘轨迹’概念，使此类系统构成独立类别。目前大多数含目标或长期规划的推荐系统，若目标明确，尚未被识别为具有独特特征而需单独归类研究。本文回顾相关工作，分析其与现有推荐系统的差异，并基于控制理论勾勒出可能的理论框架。最后，展示教育推荐系统（ERS）——本质为长期且目标驱动——如何在所提的TBRS框架内建模。
原文摘要 · Abstract (English)
Recommender Systems (RS) are a key research domain and play an increasing role in our content-overwhelmed lives. In this paper, we explore Trajectory-Based Recommender Systems (TBRS), a subfield for which many related studies exist, yet still lacking a common framework. We argue that Control Theory provides an appropriate foundation for formalizing and solving TBRS problems. TBRS, sometimes named Long Term goal Recommender Systems, share core principles with classical RS, but at their core lies the concept of a trajectory, a defining element that makes these systems a singular category. To date, most RSs that include a notion of goal or long-term objective, when this goal is explicit, have not been recognized as having specific characteristics that make them worth regrouping under a dedicated field of research. We review related work, observe how they differ from already conceptualized RSs, and sketch the foundations of a possible theoretical framework based on control theory. Finally, we show how Educational Recommender Systems (ERS), intrinsically long-term and goal-driven, can be modeled within the proposed TBRS framework.
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