Preprocessing and Feature Selection Approach for Efficient Sentiment Analysis on Product Reviews

被引：9
|
作者：
Ghosh, Monalisa [1 ]
Sanyal, Gautam [1 ]
机构：
[1] Natl Inst Technol, Dept Comp Sci & Engn, Durgapur, W Bengal, India
来源：
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS, FICTA 2016, VOL 1 | 2017年 / 515卷
关键词：
Information retrieval; Web data analysis; Preprocessing; Opinion mining; Feature selection; N-gram model;
D O I：
10.1007/978-981-10-3153-3_72
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the recent years opinion mining plays an important role by business analyst before launching a product. Opinion mining mainly concerns about detecting and extracting the feature from various opinion rich resources like review sites, discussion forum, blogs and news corpora so on. The data obtained from those are highly unstructured in nature and very large in volume, therefore data preprocessing plays an essential role in sentiment analysis. Researchers are trying to develop newer algorithm. This research paper attempts to develop a better opinion mining algorithm and the performance has been worked out.
引用
收藏
页码：721 / 730
页数：10
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