How can a learner systematically prepare for reading a book they are interested in? In this paper,we explore how computational linguistic methods such as distributional semantics, morphological clustering, and exercise generation can be combined with graph-based learner models to answer this question both conceptually and in practice. Based on the highly structured learner model and concepts from network analysis, the learner is guided to efficiently explore the targeted lexical space. They practice using multi-gap learning activities generated from the book focused on words that are central to the targeted lexical space. As such the approach offers a unique combination of computational linguistic methods with concepts from network analysis and the tutoring system domain to support learners in achieving their individual, reading task-based learning goals.

中文翻译：

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利用分布语义组织以任务为中心的词汇学习

学习者如何系统地准备阅读他们感兴趣的书？在本文中，我们探索如何将诸如分布语义，形态学聚类和练习生成之类的计算语言方法与基于图的学​​习者模型相结合，以在概念上和实践上回答这一问题。基于高度结构化的学习者模型和网络分析概念，指导学习者有效地探索目标词汇空间。他们练习使用从书中产生的多间隙学习活动，这些活动集中于目标词汇空间的核心单词。因此，该方法将计算语言方法与网络分析和补习系统领域的概念进行了独特的结合，以支持学习者实现个人学习，