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Sentiment Analysis on User Reviews Through Lexicon and Rule-Based Approach

机译:基于词汇和基于规则的方法对用户评论的情感分析

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Computers need data and humans need information. The process of converting data into useful information needs analysis to be done onto it. Reviews of customers are valuable as they are an important source of data for multiple purposes. However, these feedbacks are subjective, so extraction of information is not an easy task. This paper presents a different method of sentiment analysis research on reviews. The main focus is the data mining from multiple trustworthy sites and categorization of this data. The results are efficient and better than available multiple approaches. The paper concludes with recommendations and future work for giving a new direction to ontology-based opinion mining.
机译:计算机需要数据,而人类则需要信息。将数据转换为有用信息的过程需要对其进行分析。对客户的评论很有价值,因为它们是用于多种目的的重要数据来源。但是,这些反馈是主观的,因此提取信息并非易事。本文提出了一种不同的评论情感分析研究方法。主要重点是从多个可信赖的站点进行数据挖掘以及对这些数据进行分类。结果是有效的,并且比可用的多种方法更好。本文最后提出了建议和未来工作,为基于本体的观点挖掘提供了新的方向。

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