Cword2vec:一种基于形态规则的词嵌入方法,用于乌尔都文本情绪分析
Saquib Khushhal1, Abdul Majid1, Syed Ali Abass1
1Department of Computer Science and Information Technology, University of Azad Jammu & Kashmir, Pakistan, Muzaffarabad, Pakistan.
PeerJ. Computer science
|September 24, 2025
概括
本研究介绍了Cword2vec,这是乌尔都语自然语言处理的新方法,通过有效处理复杂的复合词来改进情感分析. 基于形态规则的嵌入显著优于传统技术.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算语言学 计算语言学
- 机器学习 机器学习
背景情况:
- 词嵌入对于NLP至关重要,捕获语法和语义词信息.
- 乌尔都语,由超过2.31亿人讲,缺乏足够的NLP研究,特别是关于其复杂的单词结构.
- 乌尔都语不确定的词语界限和复合词的普及,对比如大字母和三字母等传统的细分方法构成了挑战.
研究的目的:
- 在NLP中解决乌尔都语复合词的挑战.
- 为乌尔都文本表示提出一种新的基于形态规则的复合词嵌入 (Cword2vec).
- 用深度学习模型评估Cword2vec在乌尔都语情绪分析中的有效性.
主要方法:
- 开发了一个基于word2vec.vec的基于形态规则的复合词嵌入 (Cword2vec) 模型.
- 应用Cword2vec用于乌尔都语文文本表示. 情绪分析任务.
- 使用长短期记忆 (LSTM),双向LSTM (BiLSTM),卷积神经网络 (CNN) 和卷积LSTM (C-LSTM) 评估了Cword2vec的性能.
- 对比Cword2vec与传统的bigram和trigram方法用于复合词识别.
主要成果:
- 拟议的Cword2vec模型在所有评估的深度学习模型中显示出卓越的性能.
- 基于形态规则的复合词嵌入显著超过了传统的大字母和三字母方法.
- 在关键指标中观察到改善,包括精度,回忆,F1得分和准确性.
结论:
- 与传统方法相比,基于形态规则的复合词嵌入为乌尔都语NLP任务提供了更有效的方法.
- Cword2vec为处理乌尔都语复杂的单词结构提供了一个强大的解决方案,增强了情感分析.
- 对乌尔都语NLP进行进一步的研究,特别是具有形态学的见解,是有必要的,以利用其语言丰富性.
相关概念视频
01:29UV–Vis Spectroscopy: Woodward–Fieser Rules
28.1K
UV–Visible absorption spectra of conjugated dienes arise from the lowest energy π → π* transitions. The light-absorbing part of the molecule is called the chromophore, and the substituents directly attached to the chromophore are called auxochromes. A strong correlation exists between the absorption maxima, λmax, and the structure of a conjugated π system. The Woodward–Fieser rules predict the value of λmax for a given structure by adding the...
28.1K
01:33Proteomics
9.3K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
9.3K
02:05Degree of Unsaturation
10.4K
The degree of unsaturation (U), or index of hydrogen deficiency (IHD), is defined as the difference in the number of pairs of hydrogen atoms between the compound and the acyclic alkane with the same number of carbon atoms. Each double bond or ring costs two hydrogen atoms compared to a saturated analog and results in one degree of unsaturation.
The degree of unsaturation for hydrocarbons is U = (2C + 2 − H) / 2, where C is the number of carbon atoms and H is the number of hydrogen atoms.
The degree of unsaturation for hydrocarbons is U = (2C + 2 − H) / 2, where C is the number of carbon atoms and H is the number of hydrogen atoms.
10.4K
02:34Empathy
10.0K
Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor.
10.0K
01:30Classification of Signals
1.3K
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...
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...
1.3K
00:57Weighted Mean
6.2K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
6.2K