基于语义推理的学习资源推荐

Learning resources recommendation based on semantic reasoning

为了能够更好的满足用户对学习资源个性化的需求,在传统推荐技术的基础上,引入本体来描述学习资源,借鉴语义网中的语义联系、Spreading Activation等技术,得到更多与用户兴趣偏好有"隐藏"语义联系的资源,从用户角度保证了用户对学习资源日益增长的需求。实例验证了通过这种方法可以获得更多符合用户需求的学习资源,丰富了最终的推荐集,更好的完成个性化推荐,拓宽了用户的学习范围。

To meet the increasing demands of learning resources for users, both ontology and semantic reasoning techniques are introduced to find more resources that have hidden semantic association with user＇s preferences based on traditional recommenda- tion. The example shows that the proposed personalized recommendation strategy can diversify the final results and allow the us ers to have more choices in the learning resources. Meanwhile, the scope of learning is broadened by this method.