Aspect level sentiment analysis using machine learning

14th International Conference on Science, Engineering and Technology

自然科学;工业技术

Shubham, D.^1 ; Mithil, P.^1 ; Shobharani, Meesala^1 ; Sumathy, S.^1

School of Information Technology and Engineering, VIT University, Vellore

632014, India^1

关键词: Online shopping;    Part Of Speech;    Pre-processing operations;    System use;    Tokenization;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/263/4/042009/pdf
DOI  :  10.1088/1757-899X/263/4/042009

来源: IOP

【 摘 要 】

In modern world the development of web and smartphones increases the usage of online shopping. The overall feedback about product is generated with the help of sentiment analysis using text processing.Opinion mining or sentiment analysis is used to collect and categorized the reviews of product. The proposed system uses aspect leveldetection in which features are extracted from the datasets. The system performs pre-processing operation such as tokenization, part of speech and limitization on the data tofinds meaningful information which is used to detect the polarity level and assigns rating to product. The proposed model focuses on aspects to produces accurate result by avoiding the spam reviews.