An Analysis of Text Mining in Big Data

IF 2.8 4区 生物学
3 Biotech Pub Date : 2023-08-08 DOI:10.46632/jdaai/2/3/8
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引用次数: 0

Abstract

The practice of extracting hidden predictive information from a database and structuring it for later use is known as data mining. Web mining, text mining, sequence mining, graph mining, temporal data mining, spatial data mining, distributed data mining, and multimedia mining are some of the diverse domains in data mining. Financial data analysis, the retail and telecommunications sectors, science and engineering, and intrusion detection and prevention are a few fields where data mining is used. Worldwide, big data analytics is a burgeoning research field in computer science and many other fields. We covered text mining methods and their uses in this paper. Text mining is becoming a significant topic of study. Text mining is the process of automatically finding new, previously undiscovered information using a computer.
大数据中的文本挖掘分析
从数据库中提取隐藏的预测信息并将其结构化以供以后使用的做法被称为数据挖掘。Web挖掘、文本挖掘、序列挖掘、图挖掘、时间数据挖掘、空间数据挖掘、分布式数据挖掘和多媒体挖掘是数据挖掘的一些不同领域。金融数据分析、零售和电信部门、科学和工程以及入侵检测和防御是使用数据挖掘的几个领域。在全球范围内,大数据分析是计算机科学和许多其他领域的新兴研究领域。我们在本文中介绍了文本挖掘方法及其使用。文本挖掘正在成为一个重要的研究课题。文本挖掘是使用计算机自动发现新的、以前未发现的信息的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
3 Biotech
3 Biotech BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
自引率
0.00%
发文量
314
期刊介绍: 3 Biotech publishes the results of the latest research related to the study and application of biotechnology to: - Medicine and Biomedical Sciences - Agriculture - The Environment The focus on these three technology sectors recognizes that complete Biotechnology applications often require a combination of techniques. 3 Biotech not only presents the latest developments in biotechnology but also addresses the problems and benefits of integrating a variety of techniques for a particular application. 3 Biotech will appeal to scientists and engineers in both academia and industry focused on the safe and efficient application of Biotechnology to Medicine, Agriculture and the Environment.
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