基于云计算视角的NLP技术金融机构大数据专题分析:系统文献综述

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Information (Switzerland) Pub Date : 2023-10-20 DOI:10.3390/info14100577
Ratnesh Kumar Sharma, Gnana Bharathy, Faezeh Karimi, Anil V. Mishra, Mukesh Prasad
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引用次数: 0

摘要

本文献综述探讨了将主题分析自然语言处理技术应用于云环境中的金融数据的现有工作和实践。这项工作旨在改善大数据系统的五个v中的两个。我们使用PRISMA方法(系统评价和荟萃分析的首选报告项目)进行评价。我们使用基于关键字的搜索和文献计量分析分析了过去10年发表的关于该主题的研究论文。系统文献综述分多个阶段进行,首先根据标题和摘要进行筛选,然后根据方法/结论进行筛选,最后在阅读全文后进行筛选。然后审议了其余的文件,并在此讨论。我们发现,通过对云环境中的金融数据应用基于nlp的主题分析,可以增强自动化数据发现方法。这可以帮助识别正确的分类/分类,并衡量情感分析的数据质量。
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Thematic Analysis of Big Data in Financial Institutions Using NLP Techniques with a Cloud Computing Perspective: A Systematic Literature Review
This literature review explores the existing work and practices in applying thematic analysis natural language processing techniques to financial data in cloud environments. This work aims to improve two of the five Vs of the big data system. We used the PRISMA approach (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for the review. We analyzed the research papers published over the last 10 years about the topic in question using a keyword-based search and bibliometric analysis. The systematic literature review was conducted in multiple phases, and filters were applied to exclude papers based on the title and abstract initially, then based on the methodology/conclusion, and, finally, after reading the full text. The remaining papers were then considered and are discussed here. We found that automated data discovery methods can be augmented by applying an NLP-based thematic analysis on the financial data in cloud environments. This can help identify the correct classification/categorization and measure data quality for a sentiment analysis.
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来源期刊
Information (Switzerland)
Information (Switzerland) Computer Science-Information Systems
CiteScore
6.90
自引率
0.00%
发文量
515
审稿时长
11 weeks
期刊最新文献
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