A New Effective Criterion to Select Sentences in Extractive Text Summarization
作者： Maryam Kiabod , Sayed Mehran Sharafi , Mohammad Naderi Dehkordi
DOI:
关键词: Statistical criterion 、 Automatic summarization 、 Natural language processing 、 Artificial intelligence 、 Text segmentation 、 Text graph 、 Information retrieval 、 Sentence extraction 、 Text mining 、 Computer science 、 Position (vector) 、 Sentence
摘要: This paper introduces a new criterion to get better performance in selecting the most important sentences of text for extractive summarization. There are two kinds criteria find relevant text: statistical and semantic relations between sentences. The proposed technique is criterion. idea behind our approach consider position sentence words relative occurring title keywords. We evaluate this combination with other criteria. results show that using has good
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