The discourse-level structure of empirical abstracts: an exploratory study
Information Processing and Management: an International Journal
Towards the use of situational information in information retrieval
Journal of Documentation
Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
Robustness beyond shallowness: incremental deep parsing
Natural Language Engineering
International Journal of Intelligent Systems - Computational Models of Natural Argumentation
Text-level structure of research papers: implications for text-based information processing systems
IRSG'97 Proceedings of the 19th Annual BCS-IRSG conference on Information Retrieval Research
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
Learning analytics to identify exploratory dialogue within synchronous text chat
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
An interactive analytic tool for peer-review exploration
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
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The evaluation of scientific performance is gaining importance in all research disciplines. The basic process of the evaluation is peer reviewing, which is a time-consuming activity. In order to facilitate and speed up peer reviewing processes we have developed an exploratory NLP system in the field of educational sciences. The system highlights key sentences, which are supposed to reflect the most important threads of the article The highlighted sentences offer guidance on the content-level while structural elements -- the title, abstract, keywords, section headings -- give an orientation about the design of the argumentation in the article. The system is implemented using a discourse analysis module called concept matching applied on top of the Xerox Incremental Parser, a rule-based dependency parser. The first results are promising and indicate the directions for the future development of the system.