Learning from class-imbalanced data: Review of methods and applications
Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …
humans' decision-making responses. Detecting rare events can be viewed as a prediction …
Factors affecting online purchase intention: the case of e-commerce on lazada
PV Le-Hoang - Independent Journal of Management & …, 2020 - paulorodrigues.pro.br
This study aims to explore the scale and measure of the impact of factors affecting theonline
shopping intention of the consumer on the Lazada e-commerce website in Ho Chi Minh City …
shopping intention of the consumer on the Lazada e-commerce website in Ho Chi Minh City …
[PDF][PDF] Incorporating Dwell Time in Session-Based Recommendations with Recurrent Neural Networks.
ABSTRACT Recurrent Neural Networks (RNN) is a frequently used technique for sequence
data predictions. Recently, it gains popularity in the Recommender Systems domain …
data predictions. Recently, it gains popularity in the Recommender Systems domain …
Will this session end with a purchase? Inferring current purchase intent of anonymous visitors
Understanding the online behavior and intent of online visitors is the subject of a long line of
research. mechanisms to understand the purchase intent of visitors, to increase the number …
research. mechanisms to understand the purchase intent of visitors, to increase the number …
Session-based recommendations using item embedding
A Greenstein-Messica, L Rokach… - Proceedings of the 22nd …, 2017 - dl.acm.org
Recent methods for learning vector space representations of words, word embedding, such
as GloVe and Word2Vec have succeeded in capturing fine-grained semantic and syntactic …
as GloVe and Word2Vec have succeeded in capturing fine-grained semantic and syntactic …
Dynamic Bayesian Network–Based Product Recommendation Considering Consumers' Multistage Shopping Journeys: A Marketing Funnel Perspective
Recommender systems are widely used by online merchants to find the products that are
likely to interest consumers, but existing dynamic methods still face challenges regarding …
likely to interest consumers, but existing dynamic methods still face challenges regarding …
Using Word2Vec recommendation for improved purchase prediction
R Esmeli, M Bader-El-Den… - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Purchase prediction can help e-commerce planners plan their stock and personalised offers.
Word2Vec is a well-known method to explore word relations in sentences for sentiment …
Word2Vec is a well-known method to explore word relations in sentences for sentiment …
The dynamics of online consumers' response to price promotion
Y Kim, R Krishnan - Information Systems Research, 2019 - pubsonline.informs.org
We aim to understand the attitudinal and behavior states of the online consumer–retailer
relationship and its dynamics and, furthermore, to examine how consumers respond to price …
relationship and its dynamics and, furthermore, to examine how consumers respond to price …
Considering temporal aspects in recommender systems: a survey
The widespread use of temporal aspects in user modeling indicates their importance, and
their consideration showed to be highly effective in various domains related to user …
their consideration showed to be highly effective in various domains related to user …
Modeling the heterogeneous duration of user interest in time-dependent recommendation: A hidden semi-Markov approach
Recommender systems are widely used for suggesting books, education materials, and
products to users by exploring their behaviors. In reality, users' preferences often change …
products to users by exploring their behaviors. In reality, users' preferences often change …