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
Ratnesh Kumar Sharma, Gnana Bharathy, Faezeh Karimi, Anil V. Mishra, Mukesh Prasad
{"title":"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","authors":"Ratnesh Kumar Sharma, Gnana Bharathy, Faezeh Karimi, Anil V. Mishra, Mukesh Prasad","doi":"10.3390/info14100577","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Thematic Analysis of Big Data in Financial Institutions Using NLP Techniques with a Cloud Computing Perspective: A Systematic Literature Review\",\"authors\":\"Ratnesh Kumar Sharma, Gnana Bharathy, Faezeh Karimi, Anil V. Mishra, Mukesh Prasad\",\"doi\":\"10.3390/info14100577\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":38479,\"journal\":{\"name\":\"Information (Switzerland)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information (Switzerland)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/info14100577\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information (Switzerland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/info14100577","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信