Extraction Automatic Text Summarization Generation Method Based on Improved TextRank
TextRank,an automatic text summarization model,performs relatively well in the extraction automatic summariza-tion method,but there is still much room for adjustment and improvement in the two links of initial text quality and node weight score calculation.In view of this situation,a new adjustment method is proposed.Combined with the practical application environ-ment of automatic summarization and the literary expression characteristics of the text,the main idea of the text is highlighted and the quality of the input text is improved by adding a pre-sorting process in the text preprocessing stage.By adjusting the similarity calculation formula,factors such as word frequency,similarity with title,and position between segments are added to the weight co-efficient according to a specific proportion in the final node score formula to participate in the score calculation,so as to optimize the whole calculation process.The final experimental results show that the adjusted model is better than the original model in all as-pects.
extractiveautomatic text summarizationTextRankpre-sortingweight score
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