Analysis on Various Machine Learning based Approaches with a Perspective on the Performance

被引:0
|
作者
Rani, Meesala Shobha [1 ]
Sumathy, S. [2 ]
机构
[1] VIT Univ, Sch Comp Sci & Engn, Vellore, Tamil Nadu, India
[2] VIT Univ, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India
关键词
Machine Learning; Supervised; Semi-supervised; Unsupervised; Sentiment Analysis; SENTIMENT ANALYSIS; FEATURE-SELECTION; TEXT CATEGORIZATION; CLASSIFICATION; REVIEWS; PREDICTION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the rapid development of web 2.0, increased users of online social media show keen interest to express their opinion and reviews on numerous aspects such as microblogs, various products, hotels, movies and political issues. At present, text mining plays a vital role in various application domains such as online media, healthcare, security applications, business, marketing and industrial applications. In text mining, sentiment analysis or opinion mining is a task carried over to extract or classify the information. This paper presents an exhaustive study on the performance factors highlighting the current state-of art techniques and the open issues on various machine learning based text mining approaches.
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页数:7
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