DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-5,Issue-6 ( Jun, 2018 ) | |||||||||
Paper Title |
A Survey on Text Mining and Machine Learning Techniques for Product Review Classification | |||||||||
Author Name |
Abhijit Vakte, Nishad Tardalkar, Damini Thorat, Ratanraj Sankeshwari, Madhuri Karnik | |||||||||
Affilition |
UG Student, Vishwakarma Institute of Information Technology. Pune, Assistant Professor, Vishwakarma Institute of Information Technology. Pune | |||||||||
Pages |
54-57 | |||||||||
Abstract |
Expansion in Communication resulted large amount of real time text data being generated these days. In order to exploit and to extract useful information, it has become imperative to organize this data. Text mining / Text classification can be considered as an effective and efficient solution to this problem. Text mining can be described as a knowledge intensive process used to extract useful information from text data by exploring new patterns. It uses algorithms to transform text into data that can be analyzed by applying Machine Learning and NLP techniques. As text mining is rapidly evolving and growing technology, it facilitates businesses and companies to get deeper insights into their customer base and assist them in re-evaluating the customer demands. As the prominence of E-commerce is increasing rapidly, the number of customer reviews and feedbacks received is growing rapidly over the period of time. The number of reviews can be in thousands, making it difficult for the manufacturers to consider them all for product improvement and consumer support. This article focuses on this issue and attempts to extract some useful information from the customer reviews and ratings that can be used is enhancing the product quality and improving the consumer support which intern improves the overall customer experience. Keywords - E-Commerce, Machine Learning, Product Quality, Text Mining | |||||||||
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