运用分布语义学组织以任务为中心的词汇学习
Employing distributional semantics to organize task-focused vocabulary learning
摘要：
学习者如何系统地准备阅读他们感兴趣的书？在本文中，我们将探讨如何计算语言学方法，如分布语义，形态聚类和练习生成可以结合基于图的学习模型来回答这个问题，在概念上和实践中。基于高度结构化的学习者模型和网络分析的概念，引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，重点是对目标词汇空间至关重要的单词。因此，该方法提供了一个独特的计算语言学方法与网络分析和辅导系统域的概念相结合，以支持学习者实现他们的个人，阅读任务为基础的学习目标。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
