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Extraction: Advanced Methods00:56

Extraction: Advanced Methods

433
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
433
Social Exchange Theory02:06

Social Exchange Theory

34.4K
We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
34.4K
MicroRNAs01:22

MicroRNAs

3.0K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
3.0K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.3K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.3K
Cluster Sampling Method01:20

Cluster Sampling Method

11.8K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.8K
Convenience Sampling Method00:55

Convenience Sampling Method

8.8K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
8.8K

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相关实验视频

Updated: Jun 15, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

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三重版:从微博文本中提取知识.

Vanni Zavarella1, Sergio Consoli2, Diego Reforgiato Recupero1

  • 1Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, Cagliari, 09121, Italy.

Heliyon
|August 26, 2024
PubMed
概括

本研究介绍了一种先进的信息提取管道,用于从社交媒体创建知识图表. 该系统有效地从微博客帖子中提取开放域的实体和关系,实现高精度.

关键词:
层次化的集群化 层次化的集群化提取信息 提取信息知识图是知识图.命名实体认可 命名实体认可社交媒体分析字体嵌入式 字体嵌入式

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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科学领域:

  • 自然语言处理自然语言处理.
  • 数据科学数据科学数据科学
  • 人工智能的人工智能

背景情况:

  • 现有的知识图提取方法与社交媒体等开放域文本源相斗争.
  • 微博帖子包含独特的实体和关系,这些实体和关系不易被当前的管道模拟.

研究的目的:

  • 开发一个增强的信息提取管道,用于从微博数据中构建知识图表.
  • 为了应对在社交媒体中建模开放领域实体和关系的挑战.

主要方法:

  • 杆依赖分析用于增强信息提取.
  • 在关系分类的文字嵌入中使用无监督的等级分类.
  • 将管道应用于关于数字化转型的10万条推文.

主要成果:

  • 在提取语义三位数时,获得了超过95%的精度.
  • 精度大约比同类管道高出5%.
  • 与现有方法相比,产生了更多的三倍数.

结论:

  • 拟议的管道有效地从社交媒体中提取知识图.
  • 该系统在开放域信息提取方面表现出卓越的性能和效率.
  • 生成的知识图和方法公开用于进一步研究.