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相关概念视频

Multiple Bar Graph01:07

Multiple Bar Graph

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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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Ogive Graph01:07

Ogive Graph

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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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Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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GIS Software, Hardware, and Sources of GIS Data01:23

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A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
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Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

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It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
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Updated: Jul 13, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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一个解决方案和实践,用于结合多源异质数据,构建企业知识图.

Chenwei Yan1,2, Xinyue Fang3, Xiaotong Huang1,2

  • 1School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing, China.

Frontiers in big data
|October 16, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了一个框架,从各种数据源中构建企业知识图,增强人工智能基础设施. 这种方法提高了数据质量,并扩展了知识图.

关键词:
企业知识图表 企业知识图表图形数据库中的图形数据库.不同质的数据是不同的数据.知识图的构建知识图的构建.更新知识图表的更新

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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相关实验视频

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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

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科学领域:

  • 人工智能的人工智能
  • 知识工程知识工程知识工程
  • 数据科学数据科学数据科学

背景情况:

  • 从多个来源的异质数据构建高质量的域知识图带来了重大挑战.
  • 知识图是人工智能应用程序的重要基础设施.
  • 现有的方法往往难以有效地整合各种数据类型.

研究的目的:

  • 通过整合结构化和非结构化数据,提出构建域知识图的综合框架.
  • 提高知识图的质量和延长知识图的生命周期.
  • 在企业尽职调查中展示企业知识图的实际应用.

主要方法:

  • 开发了一个完整的过程框架,包括数据处理,信息提取,知识融合,数据存储和更新策略.
  • 企业知识图的综合企业注册,诉讼和公告信息.
  • 改进了从非结构化文本中提取三位数的现有模型,达到F1得分72.77%.

主要成果:

  • 构建了一个企业知识图,有1,430,000个节点和3,170,000个边缘.
  • 针对多源异质数据,应用了信息提取和数据存储的特定方法.
  • 进行了对图形数据库的比较分析.

结论:

  • 拟议的框架为域知识图构建提供了一个实际的解决方案.
  • 开发的企业知识图部署并用于企业尽职调查.
  • 及时更新和信息化的知识图表满足关键的业务需求.