文本分析方法及其应用综述

IF 0.4 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Data Mining Modelling and Management Pub Date : 2021-11-10 DOI:10.46610/jodmm.2021.v06i03.003
N. Ranjan, R. Prasad, D. Mane
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引用次数: 0

摘要

大约80%的组织数据以非结构化(文本)格式存在。电子邮件、社交媒体、笔记和各种不同类型的文本格式文档都存在,但所有这些数据都没有得到重视和有意义的分析。据观察,信息工作者花费大量时间(多达三分之一)来定位这些信息并试图理解它们。文本分析(TA)是分析所有这些可用的非结构化文本信息并将其转换为有用信息的过程,这些信息对组织的业务流程有很大帮助。本文讨论了文本分析的商业价值、文本分析的方法以及文本分析的商业应用。
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A Brief Survey on Text Analytics Methods and Applications
About 80% organizational data are present in the unstructured (Text) format. E-mails, Social media, notes, and wide variety of different types of documents in text formats are present, but all these data are not got importance and analyzed in meaningful ways. It has been observed that information workers spend their significant time (up to one third) to locating this information and trying to make sense of it. Text analytics (TA) is the process which analyzed all these available unstructured text information and converts it into useful information which helps the organization significantly in their business processes. In this paper we have discussed the business values, methods of text analytics, and business application of text analytics.
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来源期刊
International Journal of Data Mining Modelling and Management
International Journal of Data Mining Modelling and Management COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.10
自引率
0.00%
发文量
22
期刊介绍: Facilitating transformation from data to information to knowledge is paramount for organisations. Companies are flooded with data and conflicting information, but with limited real usable knowledge. However, rarely should a process be looked at from limited angles or in parts. Isolated islands of data mining, modelling and management (DMMM) should be connected. IJDMMM highlightes integration of DMMM, statistics/machine learning/databases, each element of data chain management, types of information, algorithms in software; from data pre-processing to post-processing; between theory and applications. Topics covered include: -Artificial intelligence- Biomedical science- Business analytics/intelligence, process modelling- Computer science, database management systems- Data management, mining, modelling, warehousing- Engineering- Environmental science, environment (ecoinformatics)- Information systems/technology, telecommunications/networking- Management science, operations research, mathematics/statistics- Social sciences- Business/economics, (computational) finance- Healthcare, medicine, pharmaceuticals- (Computational) chemistry, biology (bioinformatics)- Sustainable mobility systems, intelligent transportation systems- National security
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