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制造:多曲率适应嵌入用于时间知识图完成.

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    本研究介绍了用于时间知识图完成 (TKGC) 的多曲率自适应嵌入 (MADE). 通过利用多个曲率空间,MADE有效地建模复杂的时间知识图,优于现有方法.

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    科学领域:

    • 人工智能的人工智能
    • 数据科学数据科学数据科学
    • 知识表示 知识表示

    背景情况:

    • 时间知识图 (TKG) 对于理解不断变化的信息至关重要.
    • 传统的嵌入方法与TKG复杂的几何结构和时间依赖性质作斗争.
    • 现有的时间知识图完成 (TKGC) 模型面临着高维,非线性数据的挑战.

    研究的目的:

    • 提出一个新的TKGC模型,多曲率自适应嵌入 (MADE),能够处理TKG中的复杂几何结构.
    • 为了解决仅在欧几里德空间中嵌入TKG的局限性.
    • 为了提高TKGC的准确性和稳定性.

    主要方法:

    • 开发了MADE,这是一个嵌入TKG在多曲率空间 (欧几里德式,超标,超球) 的模型.
    • 采用数据驱动权重,以适应地利用不同的曲率空间.
    • 引入了四重分发器 (QD),以在几何空间内增强信息交互.
    • 实施了创新的时间规范化,以确保时间嵌入的流性.

    主要成果:

    • 在实验中,MADE与最先进的TKGC模型相比,表现优越.
    • 多曲率方法有效地捕捉了TKG内的各种几何结构.
    • 适应加权和时间调整显著改善了嵌入质量.

    结论:

    • MADE为时间知识图完成提供了一种强大的新方法.
    • 在多曲率空间中建模TKG对于复杂,不断发展的知识更有效.
    • 提出的方法提高了时间知识图的表示和完成.