摘要翻译：
领域专家应该为智能教学系统(ITS)提供相关的领域知识，以便在解决问题的学习活动中指导学习者。然而，对于许多定义不明确的领域，领域知识难以显式定义。在以前的工作中，我们展示了如何使用顺序模式挖掘从记录的用户交互中提取部分问题空间，以及如何在问题解决练习中支持辅导服务。本文描述了该方法的扩展，以提取更丰富、更适合于支持辅导服务的问题空间。我们将序列模式挖掘与（1）维模式挖掘（2）时间间隔挖掘（3）有值动作的自动聚类和（4）闭序列挖掘相结合。一些辅导服务已经实现，并在一个辅导系统中进行了实验。
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英文标题：
《A Knowledge Discovery Framework for Learning Task Models from User
  Interactions in Intelligent Tutoring Systems》
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作者：
P. Fournier-Viger, R. Nkambou and E. Mephu Nguifo
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最新提交年份：
2009
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  Domain experts should provide relevant domain knowledge to an Intelligent Tutoring System (ITS) so that it can guide a learner during problemsolving learning activities. However, for many ill-defined domains, the domain knowledge is hard to define explicitly. In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions, and how it can support tutoring services during problem-solving exercises. This article describes an extension of this approach to extract a problem space that is richer and more adapted for supporting tutoring services. We combined sequential pattern mining with (1) dimensional pattern mining (2) time intervals, (3) the automatic clustering of valued actions and (4) closed sequences mining. Some tutoring services have been implemented and an experiment has been conducted in a tutoring system.
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PDF链接：
https://arxiv.org/pdf/0901.4761