Smartphone app usage analysis: datasets, methods, and applications
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …
users has increased dramatically over the last decade. These personal devices, which are …
SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization
Motivation Thanks to the increasing availability of drug–drug interactions (DDI) datasets and
large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using …
large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using …
Counterfactual and factual reasoning over hypergraphs for interpretable clinical predictions on ehr
Abstract Electronic Health Record modeling is crucial for digital medicine. However, existing
models ignore higher-order interactions among medical codes and their causal relations …
models ignore higher-order interactions among medical codes and their causal relations …
3dgcn: 3-dimensional dynamic graph convolutional network for citywide crowd flow prediction
Crowd flow prediction is an essential task benefiting a wide range of applications for the
transportation system and public safety. However, it is a challenging problem due to the …
transportation system and public safety. However, it is a challenging problem due to the …
Tackling higher-order relations and heterogeneity: Dynamic heterogeneous hypergraph network for spatiotemporal activity prediction
C Tian, Z Zhang, F Yao, Z Guo, S Yan, X Sun - Neural Networks, 2023 - Elsevier
Spatiotemporal activity prediction aims to predict user activities at a particular time and
location, which is applicable in city planning, activity recommendations, and other domains …
location, which is applicable in city planning, activity recommendations, and other domains …
[HTML][HTML] Hypergraph transformers for ehr-based clinical predictions
Electronic health records (EHR) data contain rich information about patients' health
conditions including diagnosis, procedures, medications and etc., which have been widely …
conditions including diagnosis, procedures, medications and etc., which have been widely …
Spatiotemporal-aware session-based recommendation with graph neural networks
Session-based recommendation (SBR) aims to recommend items based on user behaviors
in a session. For the online life service platforms, such as Meituan, both the user's location …
in a session. For the online life service platforms, such as Meituan, both the user's location …
MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings
In recent years, predicting mobile app usage has become increasingly important for areas
like app recommendation, user behaviour analysis, and mobile resource management …
like app recommendation, user behaviour analysis, and mobile resource management …
User consumption intention prediction in meituan
For online life service platforms, such as Meituan, user consumption intention, as the internal
driving force of consumption behaviors, plays a significant role in understanding and …
driving force of consumption behaviors, plays a significant role in understanding and …
Efflex: Efficient and Flexible Pipeline for Spatio-Temporal Trajectory Graph Modeling and Representation Learning
In the landscape of spatio-temporal data analytics effective trajectory representation learning
is paramount. To bridge the gap of learning accurate representations with efficient and …
is paramount. To bridge the gap of learning accurate representations with efficient and …