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相关概念视频

Time-Series Graph00:54

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Multiple Bar Graph01:07

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As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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Vector Algebra: Graphical Method01:10

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Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
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相关实验视频

Updated: Jun 1, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

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用于链接预测的时间多模式知识图表生成.

Yuandi Li1, Hui Ji1, Fei Yu2

  • 1Jiangsu University, Zhenjiang, 212013, China.

Neural networks : the official journal of the International Neural Network Society
|January 19, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了临时多模式知识图生成 (TMMKGG) 以自动构建复杂的动态知识图. 还提出了一种新的时间多模式链路预测 (TMMLP) 方法,其性能优于现有技术.

关键词:
知识图表的生成知识图表的生成链接预测链接预测多模式知识图表多模式知识图表时间知识图表的时间知识图.

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Last Updated: Jun 1, 2025

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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:

  • 时间多模式知识图 (TMMKGs) 集成了时间多模式知识图 (TKGs) 和多模式知识图 (MMKGs).
  • TMMKGs对于模拟来自异质的时间序列数据源的动态现实世界现象至关重要.
  • 应用包括电子商务,场景录制和智能交通系统.

研究的目的:

  • 提出一种自动化的时间多模态知识图生成 (TMMKGG) 方法,以降低建设成本.
  • 引入一个动态的视听语言多模式 (VALM) 数据集,用于结构化的知识提取.
  • 开发一种时间多模连接预测 (TMMLP) 方法,以解决独特的TMMKG特征.

主要方法:

  • 开发 TMMKGG 用于自动 TMMKG 构建,专注于时间动态和跨模式集成.
  • 创建了VALM数据集,用于时间多式联接感知数据.
  • 基于TMMKGs观察到的实体边缘差异提出的TMMLP.

主要成果:

  • TMMKGG有效地生成TMMKG,与VALM数据集上的最先进的动态图形生成方法进行验证.
  • VALM数据集支持从时间多式联络数据中进行结构化知识提取.
  • 与现有方法相比,TMMLP在链接预测任务中表现优越.

结论:

  • TMMKGG提供了一种高效的方法来构建TMMKGs,减少手工劳动.
  • VALM数据集促进了对时间多式联络知识表示的研究.
  • TMMLP有效地解决了TMMKG中链接预测的独特挑战.