事件的大数据文本摘要:基于问题的学习课程

Tarek Kanan, Xuan Zhang, M. Magdy, E. Fox
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引用次数: 18

摘要

基于问题/项目的学习(PBL)是一种以学生为中心的高效教学方法,学生团队通过解决问题来学习。本文介绍了PBL在数字图书馆教育中的应用实例。我们展示了一门计算语言学课程的设计、实施、结果和部分评估,该课程为学生提供了一个积极学习的机会,让他们了解如何利用大量文本为数字图书馆增加价值,即“大数据”的一个方面。在PBL课程中,学生们将面临一个学期的挑战,即从我们的网页档案中收集大量内容,为一个事件生成良好的英语摘要。六个小组,每个小组处理不同类型的事件,并应用三种不同的总结方法,学习如何生成好的总结;相对于描述其事件的维基百科页面,它们具有相当的精确度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data Text Summarization for Events: A Problem Based Learning Course
Problem/project Based Learning (PBL) is a highly effective student-centered teaching method, where student teams learn by solving problems. This paper describes an instance of PBL applied to digital library education. We show the design, implementation, results, and partial evaluation of a Computational Linguistics course that provides students an opportunity to engage in active learning about adding value to digital libraries with large collections of text, i.e., one aspect of "big data." Students are engaging in PBL with the semester long challenge of generating good English summaries of an event, given a large collection from our webpage archives. Six teams, each working with a different type of event, and applying three different summarization methods, learned how to generate good summaries; these have fair precision relative to the Wikipedia page that describes their event.
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