Improve Manufacturing Industry Sentimental Analysis for Machine Learning

Ponniammal M Ms
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Abstract

High competitive pressure in the global manufacturing industry makes a successful, successful and sustainable development processes a successful factor. However, analyzes produced by the production control systems are defined by continuous functional improvements defined by large short-rumors. In particular, they do not use data mining to identify hidden patterns in product data. The data mining approach offered by the Advanced Production Analytics Platform is currently based on identification and method based production process optimization. Twitter is a big fast growing micro-blogging social networking platform to express their opinions about the constitution and products game. These ideas are useful for businesses, government and individuals. Therefore, tweets can be used as a valuable source for public opinion. Emotional analysis is a process to automatically identify whether a user-generated speech expresses a positive, negative or neutral point of view of a company.
改进制造业情感分析的机器学习
高竞争压力使得制造业在全球取得成功,是成功和可持续发展进程的成功因素。然而,由生产控制系统产生的分析是由持续的功能改进定义的,由大的短谣言定义。特别是,它们没有使用数据挖掘来识别产品数据中的隐藏模式。目前,先进生产分析平台提供的数据挖掘方法是基于识别和基于方法的生产过程优化。Twitter是一个快速发展的大型微博社交网络平台,用来表达人们对宪法和产品游戏的看法。这些想法对企业、政府和个人都很有用。因此,tweets可以作为一种有价值的舆论来源。情绪分析是自动识别用户生成的语音是否表达了对公司的积极、消极或中立观点的过程。
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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