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相关概念视频

Attitudes01:54

Attitudes

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Attitude is our evaluation of a person, an idea, or an object. We have attitudes for many things ranging from products that we might pick up in the supermarket to people around the world to political policies. Typically, attitudes are favorable or unfavorable: positive or negative (Eagly & Chaiken, 1993). And, they have three components: an affective component (feelings), a behavioral component (the effect of the attitude on behavior), and a cognitive component (belief and knowledge;...
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Basicity of Aromatic Amines01:18

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The basicity of aromatic amines is much weaker than that of aliphatic amines due to the involvement of the lone pair of electrons over the N atom in resonance with the aryl rings. Generally, the electron-donating ability of any substituents on the aryl ring of aromatic amines increases the basicity of the amine by increasing electron density, and hence the availability of lone pair on the nitrogen. On the other hand, electron-withdrawing functional groups on the aryl ring of amines decrease the...
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Data Collection by Observations01:08

Data Collection by Observations

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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Classification of Signals01:30

Classification of Signals

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In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
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Basicity of Aliphatic Amines01:21

Basicity of Aliphatic Amines

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Amines can behave as Brønsted–Lowry bases by accepting a proton from the acid to form corresponding conjugate acids. Due to a lone pair of nonbonding electrons, aliphatic amines can also act as Lewis bases by forming a covalent bond with an electrophile.
To measure the basicity of amines, two conventions are generally used. The first defines Kb as the basicity constant for the deprotonation reaction of water by the amine, as presented in Figure 1. Conventionally, lower Kb indicates...
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Bias01:22

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
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相关实验视频

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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面向基于情绪分析数据集的孟加拉语文本.

Mahmudul Hasan1,2, Md Rashedul Ghani1, K M Azharul Hasan1

  • 1Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh.

Data in brief
|December 6, 2024
PubMed
概括
此摘要是机器生成的。

研究人员开发了BANGLA_ABSA,这是一个新的数据集,用于以孟加拉语为基础的情感分析 (ABSA). 这个资源解决了有限数据的挑战,以分析孟加拉人的情绪.

关键词:
基于方面的情绪分析.孟加拉语情绪分析自然语言处理自然语言处理.人们的论挖掘.情绪分析是一种情绪分析.

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科学领域:

  • 自然语言处理自然语言处理.
  • 计算语言学 计算语言学
  • 社交媒体分析 社交媒体分析

背景情况:

  • 对孟加拉语社交媒体文本的情绪分析至关重要,但由于缺乏注释资源而受到阻碍.
  • 基于方面的情绪分析 (ABSA) 需要详细的数据来识别对文本中的特定方面的情绪.

研究的目的:

  • 为解决孟加拉语面向基于情绪分析 (ABSA) 的资源短缺问题.
  • 在孟加拉语中为ABSA引入高质量,手动注释的数据集.

主要方法:

  • 开发了一个名为BANGLA_ABSA.的新注释数据集.
  • 在四个领域手动注释评论:餐厅,电影,手机和汽车.
  • 数据集被组织成 {Id,Comment,Aspect Category,Sentiment Polarity} 的元组.

主要成果:

  • 创建了四个特定领域的数据集:餐厅_ABSA (801条评论),电影_ABSA (800条评论),手机_ABSA (975条评论) 和汽车_ABSA (1149条评论).
  • 所有注释的评论都是复杂的或复合的句子,提供丰富的语言数据.
  • 数据集的结构是为了在机器学习和深度学习研究中有效使用.

结论:

  • 孟加拉语_ABSA数据集是孟加拉语自然语言处理研究的重要贡献.
  • 这个资源将促进对孟加拉文本的情绪分析和机器学习的进步.
  • 允许对孟加拉语社交媒体内容进行更复杂的基于方面的情绪分析.