LRFS: online shoppers’ behavior based efficient customer segmentation model

LRFS: online shoppers’ behavior based efficient customer segmentation model

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

Bibliografiska uppgifter
Huvudupphovsman:	Khan, Riyo Hayat
Övriga upphovsmän:	Alam, Md. Golam Rabiul
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2023
Ämnen:	Customer segmentation Unsupervised machine learning K-Means K-Medoids DBSCAN RFM analysis LRFM analysis Dimensionality reduction PCA t-SNE Autoencoder Deep learning Google analytics Customer relations > Management > Data processing Machine learning Cognitive learning theory
Länkar:	http://hdl.handle.net/10361/18680

Liknande verk

Customer segmentation using K-means
av: Mahdee, Nafis, et al.
Publicerad: (2022)

LRFMV: an efficient customer segmentation model for superstores
av: Toyeb, Md., et al.
Publicerad: (2021)

3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning
av: Ahasan, Md Rakibul
Publicerad: (2022)

LRFMVD : a customer segmentation model
av: Sagor, Kawsar Mahmud, et al.
Publicerad: (2023)

Fake profile detection in social media using image processing and machine learning
av: Sen, Shuva, et al.
Publicerad: (2021)

Bangla speech recognition using 1D CNN and LSTM with different dimension reduction techniques
av: Nirjhor, S M Mahsanul Islam, et al.
Publicerad: (2019)

Gene expression analysis using machine learning
av: Mostafa, Naﬁs
Publicerad: (2021)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
av: Raizan, Syed Ahsan, et al.
Publicerad: (2021)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
av: Haque, Samiha, et al.
Publicerad: (2021)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
av: Hossain, Shoumik, et al.
Publicerad: (2022)

N.P.K. based crop suggesting model
av: Iftekher, Asif, et al.
Publicerad: (2020)

Finding ideal geographical location for businesses using machine learning technique
av: Mahmud, Mir Ibtid, et al.
Publicerad: (2022)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
av: Rahee, Arnob, et al.
Publicerad: (2021)

Classification of Bangla regional languages and recognition of artificial Bangla speech using deep learning
av: Hossain, Prommy Sultana
Publicerad: (2022)

Brain tumor detection through image processing
av: Azmim, Tahaziba, et al.
Publicerad: (2021)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
av: Sharma, Tanmoyee, et al.
Publicerad: (2021)

Prediction of coronary heart diseases using supervised machine learning algorithms
av: Salam, Nazia Binte, et al.
Publicerad: (2023)

Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN
av: Bhuiyan, Mazedul Haque, et al.
Publicerad: (2021)

Heart disease prediction using machine learning algorithms
av: Ali, Musfiq, et al.
Publicerad: (2019)

Enhancing crops production based on environmental status using machine learning techniques
av: Talukder, Shiyam, et al.
Publicerad: (2021)

Agricultural analysis and crop yield prediction of Habiganj using multispectral bands of satellite imagery with machine learning
av: Shahrin, Fariha, et al.
Publicerad: (2021)

Analysis of the impact of online education using EEG signals and machine learning algorithms
av: Hoque, Ehsanul, et al.
Publicerad: (2021)

Aspect based opinion mining on restaurant reviews
av: Tonmoy, Sazid Hasan, et al.
Publicerad: (2024)

An active-learning based training-schedule for biomedical image segmentation on deep neural networks
av: Hassan, Mehadi, et al.
Publicerad: (2021)

Public vehicle ETA system using machine learning
av: Kabir, Md. Miraz, et al.
Publicerad: (2018)

Flight fare prediction using machine learning
av: Noyon, Md. Shaim Hosan, et al.
Publicerad: (2024)

Predicting depression in Bangladeshi undergraduates using machine learning
av: Choudhury, Ahnaf Atef, et al.
Publicerad: (2019)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
av: Toufique, S.M, et al.
Publicerad: (2024)

Sentiment analysis to determine employee job satisfaction using machine learning techniques
av: Mouli, Nazifa, et al.
Publicerad: (2023)

Analyzing optimization landscape of recent policy optimization methods in deep RL
av: Khan, Mahir Asaf, et al.
Publicerad: (2023)

Breast cancer prediction using different machine learning models
av: Khandker Al- Muhaimin, et al.
Publicerad: (2020)

Automatic brain tumor segmentation using U-ResUNet chain model approach
av: Alam, Mohd Tanjeem, et al.
Publicerad: (2022)

Alumni opportunities using machine learning
av: Siaum, Arshif Sharlimin, et al.
Publicerad: (2019)

Machine learning as an indicator for breast cancer prediction
av: Shadman, Tahsin Mohammed, et al.
Publicerad: (2019)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
av: Shawan, Naveed Rahman, et al.
Publicerad: (2019)

A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images
av: Bin Mushfiq, Rahil, et al.
Publicerad: (2024)

Speech emotion detection using supervised, unsupervised and feature selection algorithms
av: Rifat, Abu Nuraiya Mahfuza Yesmin, et al.
Publicerad: (2019)

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
av: Fahim, Kaji Mehedi Hasan, et al.
Publicerad: (2024)

Observing mega cities to grow from space and predicting its growth using machine learning techniques
av: Chakma, Mitesh, et al.
Publicerad: (2018)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
av: Alhossen, Md., et al.
Publicerad: (2021)