基于物联网的农业系统情感分析实现

Q3 Chemistry
Dadheech Pankaj, R. Sheeba, R. Vidya, P. Rajarajeswari, P. Srinivasan, C. Kumar, Sudhakar Sengan
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引用次数: 0

摘要

互联网正在慢慢成为满足一个人所有需求的主要信息来源。每当有人计划购买产品时,他们往往会在网上查阅评论,从各个方面对产品有一个清晰的了解。问题是,关于单个产品的可用信息量太大,以至于用户无法从大量数据中提取他们需要的信息。本文提出了一个系统,该系统生成基于时间方面的用户意见文本摘要,这些意见是从互联网上的不同来源收集的,并带有时间戳。这些评论在预定义的基于分类后被分解为句子和子句子。然后,进行情绪分析。时间关系被考虑在内,因果关系是在意见发生重大变化的偏离点或时间范围内确定的。该系统的主要优点是,除了为客户提供一种快速、方便和简单的方式来消费产品信息以帮助他们决定是否购买产品外,还可以跟踪用户意见随时间的变化,并找出这种情绪变化的原因。它还帮助企业根据在线客户评论获得与其产品相关的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Internet of Things-Based Sentiment Analysis for Farming System
The Internet is slowly shaping to be the primary information source that fulfils all the needs of a person. Whenever someone plans to buy a product, they tend to consult with the reviews online to get a clear idea of the product in terms of its various aspects. The problem is that the information available about a single product is so much in volume that the users not be able to extract the information they require from this massive amount of data. The paper proposes a system that generates a temporal aspect based text summary of user opinions that are collected from different sources across the Internet with their time-stamp. These comments are broken into sentences and sub-sentences after predefined based classification. Then, Sentiment analysis is performed. The time relationship is taken into account, and the causal relationship is identified at the deflection points or the time frames during which there is a significant opinion change. The major advantage of this system is that the changes in user opinions with time can be traced and the cause of this sentiment change can be found out in addition to offering customers a quick, convenient and easy way to consume information about a product to help them decide whether or not to purchase it. It also helps enterprises to get relevant insights related to their products based on the customer reviews online.
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来源期刊
Journal of Computational and Theoretical Nanoscience
Journal of Computational and Theoretical Nanoscience 工程技术-材料科学:综合
自引率
0.00%
发文量
0
审稿时长
3.9 months
期刊介绍: Information not localized
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