TY  - BOOK
AU  - Hala,Balen Kamal
AU  - Çelebi,Erbuğ
TI  - USER SATISFACTION ANALYTICS USING MACHINE LEARNING TECHNIQUES
PY  - 2023///
KW  - Customer services
KW  - Dissertations, Academic
KW  - Deep learning (Machine learning)
KW  - Natural language processing (Computer science)
N1  - Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Computer Engineering Department; Includes bibliography (sheets 43-47)
N2  - ABSTRACT
Customer reviews of e-commerce service and products offering is a very critical and 
important in the business world. The e-commerce industry is driven by enormous 
data generation which is often collected for analysis and evaluation to gain both 
insight into decision making for customer purchase and also by the business 
organizations to enable them drive their businesses with informed decisions from 
customer review data. machine learning and natural language processing has gained 
so much technological development that it has been used in recent years to 
significantly contribute to the research and development of sentiment analysis of 
customer reviews and other forms of natural language processing. RNNs and LSTM 
in particular have been identified through research literature as a suitable deep 
machine learning models suitable for natural language processing due to their 
recurrent and sequential processing of data because natural language is also a 
sequential process. This study was carried out using LSTM recurrent neural network 
for Amazon polarity dataset classification, the study also applied the use natural 
language processing techniques of stemming and lemmatization which has shown 
great performance improvement compared on the experiment results, the results of 
this study was reported with an accuracy of 96%.
Keywords: Amazon Customer Reviews, Deep Learning, LSTM, Natural Language 
Processing, Recurrent Neural Network
ER  -