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http://dx.doi.org/10.14352/jkaie.2016.20.4.333

Automatic Selection of Similar Sentences for Teaching Writing in Elementary School  

Park, Youngki (School of Computer Science and Engineering, Seoul National University)
Publication Information
Journal of The Korean Association of Information Education / v.20, no.4, 2016 , pp. 333-340 More about this Journal
Abstract
When elementary students write their own sentences, it is often educationally beneficial to compare them with other people's similar sentences. However, it is impractical for use in most classrooms, because it is burdensome for teachers to look up all of the sentences written by students. To cope with this problem, we propose a novel approach for automatic selection of similar sentences based on a three-step process: 1) extracting the subword units from the word-level sentences, 2) training the model with the encoder-decoder architecture, and 3) using the approximate k-nearest neighbor search algorithm to find the similar sentences. Experimental results show that the proposed approach achieves the accuracy of 75% for our test data.
Keywords
Automatic Selection of Similar Sentences; Teaching Writing in Elementary School; Encoder-decoder Architecture;
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