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The Representativeness Heuristic02:13

The Representativeness Heuristic

17.0K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
17.0K
Ogive Graph01:07

Ogive Graph

7.1K
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...
7.1K
The Availability Heuristic01:08

The Availability Heuristic

7.2K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
7.2K
The Two-State Receptor Model01:29

The Two-State Receptor Model

3.4K
The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
The binding affinity of a drug determines its interaction with...
3.4K
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

2.4K
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
2.4K
Bar Graph01:07

Bar Graph

23.6K
A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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相关实验视频

Updated: Mar 13, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

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KGRec:一种基于注意力的知识图模型,用于推者系统.

Trinh Duong Hoan1, Bui Thanh Hung1

  • 1Data Science Laboratory, Faculty of Information Technology, Industrial University of Ho Chi Minh city, Ho Chi Minh city, Vietnam.

PloS one
|March 11, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了KGRec,这是一种使用知识图表来改进个性化内容交付的新型推模型. 通过捕捉复杂的用户-项目关系,KGRec提高了准确性和多样性,优于现有的方法.

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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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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

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相关实验视频

Last Updated: Mar 13, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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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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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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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 信息检索 信息检索

背景情况:

  • 推系统对于个性化内容提供至关重要,但往往缺乏多样性.
  • 传统的方法,如协作过,与稀疏的数据作斗争,忽略了上下文信息.
  • 提升推质量需要捕捉超出直接用户-项目交互的更高阶关系.

研究的目的:

  • 介绍KGRec,一个新的知识图注意力网络推模型.
  • 通过整合知识图表来提高建议的准确性和多样性.
  • 解决传统推系统在处理稀疏数据和上下文信息方面的局限性.

主要方法:

  • 开发了KGRec,一个集成知识图的模型,以捕捉用户,项目和属性关系.
  • 采用多层嵌入式传播和注意力机制来建模间接的用户-项目连接.
  • 利用知识图来评估关系属性的意义,以提高推质量.

主要成果:

  • 在四个基准数据集 (Yelp2018,Last-FM,Amazon-Book,MovieLen-1M) 中,KGRec的表现始终优于基线方法.
  • 该模型在建议准确性和多样性方面表现出卓越的表现.
  • 经验评估证实了KGRec在捕获更丰富的语义表示中的有效性.

结论:

  • KGRec有效地利用知识图来增强推系统.
  • 该模型的注意力机制和嵌入式传播捕捉复杂的关系,提高推质量.
  • KGRec为个性化内容提供提供了一个强大的解决方案,解决了传统方法的局限性.