对开发阿拉伯语问答系统的技术进行全面的调查
Yazeed Alkhurayyif1, Abdul Rahaman Wahab Sait2
1Department of Computer Science, Al Quwayiyah College of Sciences and Humanities, Shaqra University, Saudi Arabia.
PeerJ. Computer science
|June 22, 2023
概括
开发有效的阿拉伯语问答系统 (QAS) 需要专注于数据集和深度学习技术. 本次审查强调了无监督方法的必要性,以克服阿拉伯语QAS当前监督学习方法的局限性.
科学领域:
- 自然语言处理自然语言处理.
- 信息检索 信息检索
- 阿拉伯语语言 技术 技术
背景情况:
- 阿拉伯语是一个复杂的语言,拥有超过4.5亿的说者,对问答系统 (QAS) 提出了独特的挑战.
- 目前的阿拉伯语QAS性能往往是域特定的,限制了它们的广泛适用性.
- 人们认识到需要全面的战略来加强阿拉伯语QAS的发展.
研究的目的:
- 对开发阿拉伯语问答系统的策略进行系统的文献审查.
- 确定影响阿拉伯语QAS表现的关键因素.
- 探索阿拉伯语QAS发展中的新兴趋势和技术.
主要方法:
- 系统性文献审查方法.
- 收集和选了617篇文章,其中40篇论文被纳入最终分析.
- 对现有的阿拉伯QAS特征,分类和开发技术进行分析.
主要成果:
- 数据集质量和深度学习技术的应用对于提高阿拉伯语QAS性能至关重要.
- 目前在许多阿拉伯QAS中使用的监督学习方法导致性能限制.
- 机器学习的进步为开发无监督阿拉伯语QAS提供了机会.
结论:
- 未来的阿拉伯语QAS开发应该优先考虑强大的数据集和先进的深度学习模型.
- 探索无监督学习方法对于克服监督方法的局限性至关重要.
- 需要对阿拉伯语QAS发展战略进行进一步的研究,以满足不断变化的要求.
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