Identifying Quotations in Reference Works and Primary Materials
ECDL '08 Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries
Automatically predicting peer-review helpfulness
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Understanding differences in perceived peer-review helpfulness using natural language processing
IUNLPBEA '11 Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications
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In this paper, we use supervised machine learning to automatically identify the problem localization of peer-review feedback Using five features extracted via Natural Language Processing techniques, the learned model significantly outperforms a standard baseline Our work suggests that it is feasible for future tutoring systems to generate assessments regarding the use of localization in student peer reviews.