Exploiting Expectation Maximization Algorithm for Sentiment Analysis of Product Reviews

被引：0

作者：

Shelke, Nilesh M. ^{[1
]}

Deshpande, Shriniwas ^{[2
]}

Thakre, Vilas ^{[3
]}

机构：

[1] SGB Amravati Univ, Amravati, MS, India

[2] HVPM, DCPE, Dept Comp Sci & Technol, Amravati, MS, India

[3] SGB Amravati Univ, Dept Comp Sci & Engn, Amravati, India

来源：

PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT) | 2017年

关键词：

Expectation maximization; sentiment analysis; semantic space; log-likelihood;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Millions of comments are available on forums, Facebook, Tweeter, YouTube etc. Proper analysis of these huge comments can lead to solve many social, economic, political, business related questions which otherwise are difficult to understand and analyse. Proposed system explores the statistical approach for sentiment analysis of product reviews using expectation maximization algorithm. Systematic mathematical model has been developed for the proposed system.

引用

页码：390 / 396

页数：7

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