Customer purchase prediction from the perspective of imbalanced data: A machine learning framework based on factorization machine
Customer purchase prediction aims to predict customers' future purchases, and the
prediction results are of great importance for conducting future commercial activities. To …
prediction results are of great importance for conducting future commercial activities. To …
Distributed model for customer churn prediction using convolutional neural network
Purpose The purpose of the proposed model is to assist the e-business to predict the
churned users using machine learning. This paper aims to monitor the customer behavior …
churned users using machine learning. This paper aims to monitor the customer behavior …
Will this online shopping session succeed? predicting customer's purchase intention using embeddings
Customers are increasingly using online channels to buy products. For e-commerce
companies, this offers new opportunities to tailor the shopping experience to customers' …
companies, this offers new opportunities to tailor the shopping experience to customers' …
TEE: Real-Time Purchase Prediction Using Time Extended Embeddings for Representing Customer Behavior
Real-time customer purchase prediction tries to predict which products a customer will buy
next. Depending on the approach used, this involves using data such as the customer's past …
next. Depending on the approach used, this involves using data such as the customer's past …
Conversion prediction from clickstream: Modeling market prediction and customer predictability
As 98 percent of shoppers do not make a purchase on the first visit, we study the problem of
predicting whether they would come back for a purchase later (ie, conversion prediction) …
predicting whether they would come back for a purchase later (ie, conversion prediction) …
Predicting online purchase conversion for retargeting
Generally 2% of shoppers make a purchase on the first visit to an online store while the
other 98% enjoys only window-shopping. To bring people back to the store and close the …
other 98% enjoys only window-shopping. To bring people back to the store and close the …
A Comprehensive Bibliometric Analysis of Missing Value imputation
H Nugroho, K Surendro - IEEE Access, 2024 - ieeexplore.ieee.org
Data quality plays a crucial role in tasks, such as enhancing the accuracy of data analytics
and avoiding the accumulation of redundant data. One of the significant challenges in data …
and avoiding the accumulation of redundant data. One of the significant challenges in data …
A scalable purchase intention prediction system using extreme gradient boosting machines with browsing content entropy
Nowadays, a prosperity of electronic commerce (E-commerce) not only gives more
convenience to consumers but brings more new opportunities in online advertising and …
convenience to consumers but brings more new opportunities in online advertising and …
Predicting outcomes of active sessions using multi-action motifs
Web sites and online services increasingly engage with users through live chats to provide
support, advice, and offers. Such approaches require reliable methods to predict the user's …
support, advice, and offers. Such approaches require reliable methods to predict the user's …
High performance attack estimation in large-scale network flows
CB Freas, RW Harrison, Y Long - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Network based attacks are the major threat to security on the Internet. The volume of traffic
and the high variability of the attacks place threat detection squarely in the domain of big …
and the high variability of the attacks place threat detection squarely in the domain of big …