推进自动文本总结:释放增强的二进制多目标灰狼优化与突变
Muhammad Ayyaz Sheikh1, Maryam Bashir1, Mehtab Kiran Sudddle1
1FAST School of Computing, National University of Computer and Emerging Sciences, Lahore, Pakistan.
PloS one
|May 24, 2024
概括
自动文本摘要 (ATS) 系统从大型文本中创建简洁的摘要. 带有突变的增强二进制多目标灰狼优化器 (BMOGWO) 显著提高了ATS性能,与现有方法相比.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 自动文本总结 (ATS) 对于处理大量数据至关重要,因为手动总结是耗时和昂贵的.
- 现有的ATS系统在内容覆盖,摘要长度,冗余性和一致性方面面临挑战.
- 使用自然语言处理 (NLP) 技术,但传统方法在多方面的优化方面遇到了困难.
研究的目的:
- 为了提高自动文本总结 (ATS) 的性能.
- 引入一个改进的二进制多目标灰狼优化器 (BMOGWO) 与ATS的突变.
主要方法:
- 使用一个增强的二进制多目标灰狼优化器 (BMOGWO) 结合突变.
- 评估拟议的算法的性能与最先进的方法对比.
- 对DUC2002数据集进行测试,以进行全面评估.
主要成果:
- 增强的BMOGWO算法在ATS中表现出卓越的性能.
- 与现有的最先进的算法相比,观察到显著的改进.
- 提出的方法有效地同时解决多个总结挑战.
结论:
- 增强的BMOGWO算法代表了自动文本总结的重大进步.
- 这种方法为生成高质量,简洁的摘要提供了更有效的解决方案.
- 进一步的研究可以探索这种增强算法的应用在各种NLP任务中.
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