A Study of Big Data Processing for Sentiments Analysis

Dinesh Chander, Hari Singh, Abhinav Gupta
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引用次数: 1

Abstract

Data processing has become an important field in today's big data-dominated world. The data has been generating at a tremendous pace from different sources. There has been a change in the nature of data from batch-data to streaming-data, and consequently, data processing methodologies have also changed. Traditional SQL is no longer capable of dealing with this big data. This chapter describes the nature of data and various tools, techniques, and technologies to handle this big data. The chapter also describes the need of shifting big data on to cloud and the challenges in big data processing in the cloud, the migration from data processing to data analytics, tools used in data analytics, and the issues and challenges in data processing and analytics. Then the chapter touches an important application area of streaming data, sentiment analysis, and tries to explore it through some test case demonstrations and results.
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面向情感分析的大数据处理研究
在大数据主导的今天,数据处理已经成为一个重要的领域。数据以惊人的速度从不同的来源产生。数据的性质已经从批处理数据转变为流数据,因此,数据处理方法也发生了变化。传统的SQL不再能够处理这些大数据。本章描述了数据的本质以及处理这些大数据的各种工具、技术和技术。本章还描述了将大数据转移到云上的需求和在云上处理大数据的挑战,从数据处理到数据分析的迁移,数据分析中使用的工具,以及数据处理和分析中的问题和挑战。然后,本章触及流数据的一个重要应用领域——情感分析,并试图通过一些测试用例演示和结果来探索它。
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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