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相关概念视频

Manipulation and Analysis01:21

Manipulation and Analysis

287
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Cognitive Learning01:21

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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为协作设计:可视化使人类-LLM分析伙伴关系成为可能

Mai Elshehaly, Radu Jianu, Aidan Slingsby

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    此摘要是机器生成的。

    动态可视化对于数据分析中的有效人大语言模型 (LLM) 协作至关重要. 可视化不断发展的分析文物和来源增强了LLM辅助工作流程的透明度和洞察力.

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    科学领域:

    • 数据可视化 数据可视化
    • 人与计算机的交互
    • 人工智能的人工智能

    背景情况:

    • 视觉化文物传统上支持人类协作和知识转移在数据分析.
    • 视觉化在人类与大型语言模型 (LLM) 交互期间捕获知识的作用仍然未被充分探索.
    • 当前的LLM分析工作流通常是线性和基于文本的,阻碍了分析过程的结构化表示.

    研究的目的:

    • 调查可视化工件在人-LLM分析工作流程中的潜力.
    • 要突出目前的LLM基于文本的追踪和结构分析方法的局限性.
    • 倡导动态的视觉表示,以增强人类-LLM合作和知识外部化.

    主要方法:

    • 探索LLM在跟踪,结构化和可视化分析过程中的当前机会和局限性.
    • 在人-LLM工作流程中整合动态可视化的概念论证.
    • 根据LLM的进展,提出一个研究议程的建议.

    主要成果:

    • 在LLMs的线性基于文本的工作流程限制了分析文物的可追溯性和结构.
    • 动态视觉表示被认为是构建不断变化的文物和来源的关键.
    • 展示了使用LLM来可视化分析过程的机遇和局限性.

    结论:

    • 动态可视化对于有效的人类-LLM分析互动至关重要.
    • 可视化不断演变的文物和来源可以导致更结构化和透明的分析过程.
    • 需要进一步的研究来利用LLM的功能来增强分析中的可视化.