In the current context of scientific information overload in which new knowledge is created at a rapid pace, we propose to develop text summarization services for automatically identifying the most important information of a research article. The work will be based on an adaptation of our current scientific text mining and summarization technology at our LaSTUS/TALN lab. The summarization system will apply a natural language processing pipeline for deep analysis of scientific documents and compute a series of sentence relevance features based on the results of text analysis.
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Level of knowledge: Intermediate: able to
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This project has received funding from the European Union’s Seventh Framework Programme for research,
technological development and demonstration under grant agreement no 612425.