000			02667nam a22003017a 4500
003			KOHA
005			20230418115911.0
008			230317d2023 cy ||||| m||| 00| 0 eng d
040			_aCY-NiCIU _beng _cCY-NiCIU _erda
041			_aeng
090			_aYL 2805 _bH26 2023
100	1		_aHala, Balen Kamal
245	1	0	_aUSER SATISFACTION ANALYTICS USING MACHINE LEARNING TECHNIQUES / _cBALEN KAMAL HAMA; SUPERVISOR: PROF. DR. ERBUĞ ÇELEBI
264			_c2023
300			_aviii, 47 sheets; _c31 cm. _eIncludes CD
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
502			_aThesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Computer Engineering Department
504			_aIncludes bibliography (sheets 43-47)
520			_aABSTRACT 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
650		0	_aCustomer services _vDissertations, Academic
650		0	_aDeep learning (Machine learning) _vDissertations, Academic
650		0	_aNatural language processing (Computer science) _vDissertations, Academic
700	1		_aÇelebi, Erbuğ _esupervisor
942			_2ddc _cTS
999			_c289977 _d289977