%0 Journal Article %1 Xiong10 %A Xiong, Wenting %A Litman, Diane %D 2010 %J Lecture Notes in Computer Science %K Language Natural Processing peer-review %P 429 - 431 %T Identifying Problem Localization in Peer-Review Feedback %V 6095/2010 %X 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.

@article{Xiong10, abstract = {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.}, added-at = {2011-06-10T12:13:11.000+0200}, author = {Xiong, Wenting and Litman, Diane}, biburl = {https://www.bibsonomy.org/bibtex/20009ce77b3d68ebf169a40ad0a1b7a37/jennymac}, description = {SpringerLink - Abstract DOI:10.1007/978-3-642-13437-1_93}, interhash = {e1df9dc37bcab87e1a6ee8898b9f59a5}, intrahash = {0009ce77b3d68ebf169a40ad0a1b7a37}, journal = {Lecture Notes in Computer Science}, keywords = {Language Natural Processing peer-review}, pages = {429 - 431}, timestamp = {2011-06-10T12:13:11.000+0200}, title = {Identifying Problem Localization in Peer-Review Feedback}, volume = {6095/2010}, year = 2010 }