Attention-enhanced graph neural networks with global context for session-based recommendation
Y Chen, Y Tang, Y Yuan - IEEE Access, 2023 - ieeexplore.ieee.org
Session-based recommendation is a crucial task aiming to predict users' interested items
based only on anonymous user behaviors. Most recent solutions for session-based …
based only on anonymous user behaviors. Most recent solutions for session-based …
Beyond clicks: Modeling multi-relational item graph for session-based target behavior prediction
Session-based target behavior prediction aims to predict the next item to be interacted with
specific behavior types (eg, clicking). Although existing methods for session-based behavior …
specific behavior types (eg, clicking). Although existing methods for session-based behavior …
Benchmark data for mobile app traffic research
R Wang, Z Liu, Y Cai, D Tang, J Yang… - Proceedings of the 15th …, 2018 - dl.acm.org
Mobile app traffic classification aims to automatically map mobile packets into apps. It has
become an active task in mobile traffic engineering, and numerous algorithms have been …
become an active task in mobile traffic engineering, and numerous algorithms have been …
Ai-driven mobile apps: an explorative study
Recent years have witnessed an astonishing explosion in the evolution of mobile
applications powered by AI technologies. The rapid growth of AI frameworks enables the …
applications powered by AI technologies. The rapid growth of AI frameworks enables the …
Establishing smartphone user behavior model based on energy consumption data
In smartphone data analysis, both energy consumption modeling and user behavior mining
have been explored extensively, but the relationship between energy consumption and user …
have been explored extensively, but the relationship between energy consumption and user …
Personalized graph neural networks with attention mechanism for session-aware recommendation
The problem of session-aware recommendation aims to predict users' next click based on
their current session and historical sessions. Existing session-aware recommendation …
their current session and historical sessions. Existing session-aware recommendation …
Demographic attributes prediction through app usage behaviors on smartphones
Smartphone applications (Abbr. apps) have become an indispensable part in our everyday
lives. Users determine what apps to use depending on their personal needs and interests …
lives. Users determine what apps to use depending on their personal needs and interests …
Sume: Semantic-enhanced urban mobility network embedding for user demographic inference
Recent years have witnessed a rapid proliferation of personalized mobile applications,
which poses a pressing need for accurate user demographics inference. Facilitated by the …
which poses a pressing need for accurate user demographics inference. Facilitated by the …
Mobile app recommendation: An involvement-enhanced approach
Given the ubiquitous and critical role of mobile apps in people's lives as well as the sheer
size of the mobile app market, developing effective mobile app recommendation methods …
size of the mobile app market, developing effective mobile app recommendation methods …
A multi-task graph neural network with variational graph auto-encoders for session-based travel packages recommendation
Session-based travel packages recommendation aims to predict users' next click based on
their current and historical sessions recorded by Online Travel Agencies (OTAs). Recently …
their current and historical sessions recorded by Online Travel Agencies (OTAs). Recently …