Rating detection by reviews using ML and NLP towards mobile phone recommendation

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Detalhes bibliográficos
Principais autores:	Sarker, Md Wafi, Al Nahian, Sheikh Sanzid, Khan, Anjumand Moshtari, Oraib, Abdullah, Islam, Sikder Mohidul
Outros Autores:	Sadeque, Dr. Farig Yousuf
Formato:	Tese
Idioma:	English
Publicado em:	Brac University 2023
Assuntos:	Recommendation system Natural language processing Machine learning Deep learning Sentimental analysis Long short term memory Naive bayes Convolutional neural network Support vector machine Multi layer perceptron Gradient booster machine Stochastic gradient descent Random fores
Acesso em linha:	http://hdl.handle.net/10361/21926

id	10361-21926
record_format	dspace
spelling	10361-219262023-12-07T10:36:08Z Rating detection by reviews using ML and NLP towards mobile phone recommendation Sarker, Md Wafi Al Nahian, Sheikh Sanzid Khan, Anjumand Moshtari Oraib, Abdullah Islam, Sikder Mohidul Sadeque, Dr. Farig Yousuf Department of Computer Science and Engineering, Brac University Recommendation system Natural language processing Machine learning Deep learning Sentimental analysis Long short term memory Naive bayes Convolutional neural network Support vector machine Multi layer perceptron Gradient booster machine Stochastic gradient descent Random fores Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 48-52). Product recommendation is a type of marketing tool that has become increasingly important for businesses as well as in purchasing goods in the digital age. Prod uct recommendation is the process of suggesting items to customers based on their previous purchases or choices and is a form of personalization where the goal is to provide relevant, valuable, and timely information to customers to help them make decisions about what to buy. The purpose of product recommendations is to in crease customer engagement, loyalty, and ultimately, sales while ensuring customers help buying products according to their preference. By providing customers with personalized product recommendations, businesses are able to increase customer satisfaction and loyalty, as well as drive sales. On the other way, customers also feel secure while purchasing products according to their personality and choices. This paper builds a product recommendation system by analyzing the techniques of Machine Learning and Natural Language Processing. The focus of the research is on recommending mobile phone products to users based on their preferences and interests. The system was advanced and examined using a dataset of mobile phone specifications and user reviews. The study’s findings demonstrate that the sug gested recommendation system may offer users accurate and pertinent ideas; but, due to dataset restrictions, the system cannot be expanded to include other kinds of products. However, the proposed system can be used for taking personalized require ments and finding a better result for them with improved accuracy and precision which ultimately will enhance customer satisfaction. Md Wafi Sarker Sheikh Sanzid Al Nahian Anjumand Moshtari Khan Abdullah Oraib Sikder Mohidul Islam B.Sc. in Computer Science and Engineering 2023-12-05T09:50:55Z 2023-12-05T09:50:55Z 2023 2023-01 Thesis ID: 18101449 ID: 18101381 ID: 21101113 ID: 18301207 ID: 18101146 http://hdl.handle.net/10361/21926 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 52 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Recommendation system Natural language processing Machine learning Deep learning Sentimental analysis Long short term memory Naive bayes Convolutional neural network Support vector machine Multi layer perceptron Gradient booster machine Stochastic gradient descent Random fores Machine learning
spellingShingle	Recommendation system Natural language processing Machine learning Deep learning Sentimental analysis Long short term memory Naive bayes Convolutional neural network Support vector machine Multi layer perceptron Gradient booster machine Stochastic gradient descent Random fores Machine learning Sarker, Md Wafi Al Nahian, Sheikh Sanzid Khan, Anjumand Moshtari Oraib, Abdullah Islam, Sikder Mohidul Rating detection by reviews using ML and NLP towards mobile phone recommendation
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
author2	Sadeque, Dr. Farig Yousuf
author_facet	Sadeque, Dr. Farig Yousuf Sarker, Md Wafi Al Nahian, Sheikh Sanzid Khan, Anjumand Moshtari Oraib, Abdullah Islam, Sikder Mohidul
format	Thesis
author	Sarker, Md Wafi Al Nahian, Sheikh Sanzid Khan, Anjumand Moshtari Oraib, Abdullah Islam, Sikder Mohidul
author_sort	Sarker, Md Wafi
title	Rating detection by reviews using ML and NLP towards mobile phone recommendation
title_short	Rating detection by reviews using ML and NLP towards mobile phone recommendation
title_full	Rating detection by reviews using ML and NLP towards mobile phone recommendation
title_fullStr	Rating detection by reviews using ML and NLP towards mobile phone recommendation
title_full_unstemmed	Rating detection by reviews using ML and NLP towards mobile phone recommendation
title_sort	rating detection by reviews using ml and nlp towards mobile phone recommendation
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/21926
work_keys_str_mv	AT sarkermdwafi ratingdetectionbyreviewsusingmlandnlptowardsmobilephonerecommendation AT alnahiansheikhsanzid ratingdetectionbyreviewsusingmlandnlptowardsmobilephonerecommendation AT khananjumandmoshtari ratingdetectionbyreviewsusingmlandnlptowardsmobilephonerecommendation AT oraibabdullah ratingdetectionbyreviewsusingmlandnlptowardsmobilephonerecommendation AT islamsikdermohidul ratingdetectionbyreviewsusingmlandnlptowardsmobilephonerecommendation
_version_	1814307294554357760

Rating detection by reviews using ML and NLP towards mobile phone recommendation

Registros relacionados