A feature based approach for sentiment analysis using SVM and coreference resolution

Hari Krishna, Rahamathulla, Ali Akbar
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引用次数: 23

Abstract

Online shopping is one of the most comfortable ways to shop in this new era of technology. People buy online products frequently and post their reviews about the products they have used. The viewpoint of the user will be in the form of tweets or product reviews which they post in an e-commerce site. These reviews will have significant role in deciding how far the products have been placed in peoples mind. These reviews will also help the manufacturers to improve the features of the product as required But it is a very difficult task to manually read the reviews and assign sentiment to them. This problem can be solved by creating an automated system in which we can analyze the reviews posted by the users and extract the users perception about a particular feature. In this work we have developed a procedure for ‘feature based sentiment analysis’ by using a classifier called Support Vector Machine.
基于支持向量机和共参考分辨率的特征情感分析方法
网上购物是这个新科技时代最舒适的购物方式之一。人们经常在网上购买产品,并对他们使用过的产品发表评论。用户的观点将以他们在电子商务网站发布的tweet或产品评论的形式出现。这些评论将在决定产品在人们心目中的地位方面发挥重要作用。这些评论也将帮助制造商根据需要改进产品的功能,但手动阅读评论并为其分配情感是一项非常困难的任务。这个问题可以通过创建一个自动化系统来解决,在这个系统中,我们可以分析用户发布的评论,并提取用户对特定功能的看法。在这项工作中,我们通过使用一种称为支持向量机的分类器开发了一种“基于特征的情感分析”程序。
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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