Opinion Mining and Sentiment Classification: A Review

被引：0

作者：

Das, Manoj Kumar ^{[1
]}

Padhy, Binayak ^{[2
]}

Mishra, Brojo Kishore ^{[3
]}

机构：

[1] BPUT, Rourkela, India

[2] SPMU, ICZMP, Bhubaneswar, Orissa, India

[3] CV Raman Coll Engn, Bhubaneswar, Orissa, India

来源：

PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE SYSTEMS AND CONTROL (ICISC 2017) | 2017年

关键词：

Text mining; support vector machine (SVM); Sentiment Classification; Feature extraction; opinion mining;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the evolution of web technology, there is a huge amount of data present in the web for the internet users. These users not only use the available resources in the web, but also give their feedback, thus generating additional useful information Due to overwhelming amount of user's opinions, views, feedback and suggestions available through the web resources, it's very much essential to explore, analyze and organize their views for better decision making. Opinion Milling or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the user's views or opinions explained in the form of positive, negative or neutral comments and quotes underlying the text. Various supervised or data-driven techniques to Sentiment analysis like Na ve Byes, Maximum Entropy and SVM. For classification use support vector machine (SVM), it performs the sentiment classification task also consider sentiment classification accuracy.

引用

页码：790 / 792

页数：3

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