Abstract
Massive scientific and technical literature has recorded the developments of science and technology and contains plentiful knowledge. Researchers have to read scientific literature such as papers, patents, and reports to know the latest developments in time. However, it is difficult for researchers to read all the newly published and relevant literature. So there is an urgent need for scientific literature summarization systems to provide brief and important dynamic information that researchers are interested in. This paper proposes an approach to generate automatic summarization based on 5W1H event structure. Sentences in the literature are classified and selected for different elements of events by relevance, and then the importance of each candidate sentence is calculated. Top-k relevant and important sentences are selected to formulate event-based summarization. Comparing with existing summarization results or abstracts given by authors, experiment results of our approach contain more detailed information with the the 5W1H event structure, which is more convenient for researchers to search and browse the brief description of scientific and technical information distributed in massive scientific literature.
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