提出了一种对语义网上的本体进行检索和排序的新方法ARRO(an Approach for Retrieval and Ranking for the On-tology),其核心思想是通过对本体进行解析产生逻辑三元组.再在三元组的基础上进行逻辑推理,形成概念的逻辑视图,然后通过排序公式对相关本体进行检索和排序.这种通过逻辑视图和三元组对本体进行检索和排序的方法可以有效的进行逻辑推理,并提高检索效率,从而解决在传统的基于关键字的信息检索中只能从句法上对关键字进行分析,无法将推理和检索相互结合,互相促进的问题.本文对ARRO进行了测试,结果验证了其实用性和有效性.
Personalized education provides an open learning environment which enriches the advanced technologies to establish a paradigm shift, active and dynamic teaching and learning patterns. E-learning has a various established approaches to the creation and sequencing of content-based, single learner, and self-paced learning objects. However, there is little understanding of how to create sequences of learning activities which involve groups of learners interacting within a structured set of collaborative environments. In this paper, we present an approach for learning activity sequencing based on ontology and activity graph in personalized education system. Modeling and management of learning activity and learner are depicted, and an algorithm is proposed to realize learning activity sequencing and learner ontology dynamically updating.
