Assessing Student Paraphrases Using Lexical Semantics and Word Weighting
Assessing Student Paraphrases Using Lexical Semantics and Word Weighting
复制标题
使用词汇语义和单词权重评估学生的释义
DOI：
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发表时间：
2009
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通讯作者：
D. McNamara
中科院分区：
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作者：
V. Rus;Mihai C. Lintean;A. Graesser;D. McNamara
We present in this paper an approach to assessing student paraphrases in the intelligent tutoring system iSTART. The approach is based on measuring the semantic similarity between a student paraphrase and a reference text, called the textbase. The semantic similarity is estimated using knowledge-based word relatedness measures. The relatedness measures rely on knowledge encoded in Word-Net, a lexical database of English. We also experiment with weighting words based on their importance. The word importance information was derived from an analysis of word distributions in 2,225,726 documents from Wikipedia. Performance is reported for 12 different models which resulted from combining 3 different relatedness measures, 2 word sense disambiguation methods, and 2 word-weighting schemes. Furthermore, comparisons are made to other approaches such as Latent Semantic Analysis and the Entailer.
