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AIED
2009
Springer

Assessing Student Paraphrases Using Lexical Semantics and Word Weighting

10 years 1 months ago
Assessing Student Paraphrases Using Lexical Semantics and Word Weighting
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 WordNet, 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. Keywords. intelligent tutoring systems, natural language processing
Vasile Rus, Mihai C. Lintean, Arthur C. Graesser,
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where AIED
Authors Vasile Rus, Mihai C. Lintean, Arthur C. Graesser, Danielle S. McNamara
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