Cross-session aware temporal convolutional network for session-based recommendation
R Ye, Q Zhang, H Luo - 2020 International Conference on Data …, 2020 - ieeexplore.ieee.org
Recent advancements in Graph Neural Networks (GNN) have achieved promising results for
the session-based recommendation, which aims to predict a user's actions based on …
the session-based recommendation, which aims to predict a user's actions based on …
A novel macro-micro fusion network for user representation learning on mobile apps
The evolution of mobile apps has greatly changed the way that we live. It becomes
increasingly important to understand and model the users on mobile apps. Instead of …
increasingly important to understand and model the users on mobile apps. Instead of …
Smartphone app categorization for interest targeting in advertising marketplace
Last decade has witnessed a tremendous expansion of mobile devices, which brought an
unprecedented opportunity to reach a large number of mobile users at any point in time. This …
unprecedented opportunity to reach a large number of mobile users at any point in time. This …
Characterizing and forecasting user engagement with in-app action graph: A case study of snapchat
While mobile social apps have become increasingly important in people's daily life, we have
limited understanding on what motivates users to engage with these apps. In this paper, we …
limited understanding on what motivates users to engage with these apps. In this paper, we …
Multi-context embedding based personalized place semantics recognition
L Chen, M Han, H Shi, X Liu - Information Processing & Management, 2021 - Elsevier
Personalized place semantics recognition is the process of giving individual semantic labels
to locations, eg,“home” and “school”. Capturing personalized place semantics exactly is …
to locations, eg,“home” and “school”. Capturing personalized place semantics exactly is …
Profiling wireless resource usage for mobile apps via crowdsourcing-based network analytics
Y Ouyang, T Yan - IEEE Internet of Things Journal, 2015 - ieeexplore.ieee.org
The rapid growth of mobile app traffic brings huge pressure to today's cellular networks.
While this fact is commonly concerned by all the mobile carriers, little work has been done to …
While this fact is commonly concerned by all the mobile carriers, little work has been done to …
Mobi-SAGE-RS: A sparse additive generative model-based mobile application recommender system
With the rapid prevalence of smart mobile devices and the dramatic proliferation of mobile
applications (Apps), App recommendation becomes an emergent task that will benefit …
applications (Apps), App recommendation becomes an emergent task that will benefit …
Mobile app classification with enriched contextual information
The study of the use of mobile Apps plays an important role in understanding the user
preferences, and thus provides the opportunities for intelligent personalized context-based …
preferences, and thus provides the opportunities for intelligent personalized context-based …
DDHCN: Dual decoder Hyperformer convolutional network for Downstream-Adaptable user representation learning on app usage
F Zeng, Y Li, J Xiao, D Yang - Expert Systems with Applications, 2024 - Elsevier
In mobile scenarios, there is a need for general user representations to solve multiple target
tasks. However, there are some challenges in the related research (eg, difficulty in learning …
tasks. However, there are some challenges in the related research (eg, difficulty in learning …
Predicting and recommending the next smartphone apps based on recurrent neural network
The popularity of smartphones has witnessed the rapid growth of the number of mobile
applications. Nowadays, there are millions of applications available, and at the same time …
applications. Nowadays, there are millions of applications available, and at the same time …