GistSumm: A Summarization Tool Based on a New Extractive Method
作者： Thiago Alexandre Salgueiro Pardo , Lucia Helena Machado Rino , Maria das Graças Volpe Nunes , None
关键词: Computer science 、 Natural language processing 、 Artificial intelligence 、 Natural language 、 Data compression ratio 、 Text graph 、 Automatic summarization 、 Information retrieval 、 Textuality 、 GiST 、 Source text
摘要: This paper presents a new extractive approach to automatic summarization based on the gist of source text. The gist-based system, called GistSumm (GIST SUMMarizer), uses as guideline identify and select text segments include in final extract. Automatically produced extracts have been evaluated under light preservation textuality.
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