专利申请技术披露文件的多维融合战略相似度衡量方法
Meilong Zhu1, Mingda Li1, Kangwei Hou1
1China Telecom Research Institute, Beijing, China.
PloS one
|October 18, 2023
概括
本研究引入了一种新的多维融合策略,用于评估专利技术披露文件的相似性,比现有方法提高准确性和效率. 该方法通过提供更可靠,更快速的自动化评估系统来加强专利新性评估.
科学领域:
- 知识产权管理知识产权管理
- 计算机科学 计算机科学
- 信息检索 信息检索
背景情况:
- 专利申请技术披露文件的自动评估对于评估新性和独特性至关重要,但目前的方法面临挑战.
- 现有的文本相似性算法在有限的跨图书馆数据和对核心内容的关注不足方面扎,阻碍了实际应用.
- 人类评估是耗时和主观的,需要更客观的自动化解决方案.
研究的目的:
- 提出一种新的多维融合策略,用于对专利申请技术披露文件的相似性评估.
- 提高自动化专利相似性评估的准确性和效率.
- 提供一种可靠的专利新性和独特性判断的新方法.
主要方法:
- 开发了文本预处理策略,包括单词细分重建和单词频率和部分语音分数的加权融合.
- 引入了使用点矩阵和图像映射空间进行多样化评估的相似性计算方法.
- 对已发表的文本相似性数据集和专利申请技术披露文件的特定数据集进行了评估.
主要成果:
- 与基准数据集上的传统矢量语义模型相比,多维融合策略提高了约10%的歧视准确性.
- 该方法在不需要培训的情况下实现了与轻量级深度学习模型相似的区分能力.
- 在专利披露文件数据集上,拟议的方法表现比传统模型高20%和深度学习模型高1-8%,精度和回忆平衡.
结论:
- 拟议的多维融合战略在评估专利申请技术披露文件相似性方面取得了重大进展.
- 点矩阵和图像空间映射方法提供了有效和可靠的相似性计算.
- 这项研究为自动化专利相似性评估提供了一种有价值的新方法,改进了现有的技术.
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