A sentence selection model and HLO algorithm for extractive text summarization

R. Alguliyev, R. Aliguliyev, Nijat R. Isazade
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引用次数: 19

Abstract

In paper text summarization represented as a sentence scoring and selection process. The process is modeled as a multi-objective optimization problem. The proposed model attempts to find balance between coverage and redundancy in a summary. For solving the optimization problem a human learning optimization algorithm is utilized.
一种用于抽取文本摘要的句子选择模型和HLO算法
在论文文本摘要中表现为句子的评分和选择过程。该过程被建模为一个多目标优化问题。提出的模型试图在摘要中找到覆盖和冗余之间的平衡。为了解决优化问题,采用了人的学习优化算法。
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