本体论知识库推理的自适应学习流程规划

为了自适应提取网络上的学习资源（Learning Resources,LR）,向学习者提供可用的、有价值的LR流程规划,提出了本体论知识库推理的自适应学习流程规划方法.首先,运用知识工程中的本体论技术描述LR领域知识,建立本体论知识库;其次,使用人工智能规划技术对问题进行描述,采用偏序规划算法推理,结合工作流模型技术验证,建立规则式推理机制;最后,通过本体论知识库和规则式推理机制实现对LR的自适应提取和完成LR流程结构.对实例的规划结果表明,该方法是可靠和有效的.

Adaptive Learning Process Planning Based on Ontological KB Inference

In order to extract adaptively LR（learning resources） and provide learners with available and valuable LR process planning,this paper proposes the method of adaptive learning process planning based on ontological KB（knowledgge base） inference.Firstly,the LR domain knowledge is described by ontology in knowledge engineering to establish the ontological KB;secondly,the planning is described by artificial intelligence technology,inferred by partially-ordered planning algorithm and verified with workflow model technology to establish the rule-based reasoning mechanism;finally,the adaptive extraction of LR is realized and the LR process structure completed by the ontological KB and rule-based reasoning mechanism.The case planning results prove the method to be dependable and effective.