一种融合任务激励与语义对话模型的教育陪伴式智能体系统
By integrating task incentives and semantic dialogue models into an educational companion intelligent agent system, the problem of the separation between semantic dialogue and task incentive modules has been solved, realizing personalized and emotional learning support and improving learning efficiency and user stickiness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING HOPE ONLINE SUBJECT TRAINING SCHOOL
- Filing Date
- 2025-09-26
- Publication Date
- 2026-07-17
AI Technical Summary
In existing educational companionship intelligent agent systems, semantic dialogue and task incentive modules are separated, failing to form an effective closed loop and thus unable to provide personalized, real-time learning support.
An educational companionship-style intelligent agent system that integrates task incentives and semantic dialogue models analyzes learning needs through a semantic dialogue module, generates targeted dialogue responses, and achieves bidirectional data interaction with a task incentive module to dynamically adjust task incentive parameters. Combined with user learning profiles from a knowledge storage module, it realizes personalized incentive tasks.
It achieves a high degree of unity between personalized incentives and emotional support, dynamically adjusts task difficulty and rewards, enhances learning initiative and efficiency, reduces frustration, strengthens user stickiness, and provides truly personalized learning support.
Smart Images
Figure CN121303333B_ABST