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Providing grades and feedback for student summaries by ontology-based information extraction
2012
Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12
Automatic grading systems for summaries and essays have been studied for years. Most commercial and research implementations are based in statistical methods, such as Latent Semantic Analysis (LSA), which can provide high accuracy on similarity between the essay and the graded or standard essays, but they can offer very limited feedback. In the present work, we propose a novel method to provide both grades and meaningful feedback for student summaries by Ontology-based Information Extraction
doi:10.1145/2396761.2398505
dblp:conf/cikm/GutierrezDFG12
fatcat:4sfvgrco3rhvta73zsfpo444b4