Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
An annotation scheme for discourse-level argumentation in research articles
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Sensemaking tools for understanding research literatures: Design, implementation and user evaluation
International Journal of Human-Computer Studies
International Journal of Intelligent Systems - Computational Models of Natural Argumentation
Identifying the epistemic value of discourse segments in biology texts
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
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The exponential growth of the World Wide Web in the last decade, brought with it an explosion in the information space. One, heavily affected area is the scientific literature, where finding relevant work in a particular field, and exploring links between relevant publications represents a cumbersome task. In this paper we make the initial steps in the direction of automatic extraction of epistemic items (i.e. claims, positions, arguments) from scientific publications. Our approach will provide the foundation for a comprehensive solution that will partly alleviate the information overload problem. We detail the actual extraction process, the evaluation we have performed and relevant use-cases for our work.