Big Data Text Summarization for Events: A Problem Based Learning Course

被引:11
|
作者
Kanan, Tarek [1 ]
Zhang, Xuan [1 ]
Magdy, Mohamed [1 ]
Fox, Edward [1 ]
机构
[1] Virginia Tech, Dept Comp Sci, Blacksburg, VA 24060 USA
关键词
Problem based learning; Digital libraries; Computational linguistics; Text summarization; Big data;
D O I
10.1145/2756406.2756943
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:87 / 90
页数:4
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