Smartphone app usage analysis: datasets, methods, and applications

T Li, T Xia, H Wang, Z Tu, S Tarkoma… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …

SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization

Y Yu, K Huang, C Zhang, LM Glass, J Sun… - …, 2021 - academic.oup.com
Motivation Thanks to the increasing availability of drug–drug interactions (DDI) datasets and
large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using …

Counterfactual and factual reasoning over hypergraphs for interpretable clinical predictions on ehr

R Xu, Y Yu, C Zhang, MK Ali, JC Ho… - Machine Learning for …, 2022 - proceedings.mlr.press
Abstract Electronic Health Record modeling is crucial for digital medicine. However, existing
models ignore higher-order interactions among medical codes and their causal relations …

3dgcn: 3-dimensional dynamic graph convolutional network for citywide crowd flow prediction

T Xia, J Lin, Y Li, J Feng, P Hui, F Sun, D Guo… - ACM Transactions on …, 2021 - dl.acm.org
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 …

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 …

[HTML][HTML] Hypergraph transformers for ehr-based clinical predictions

R Xu, MK Ali, JC Ho, C Yang - AMIA Summits on Translational …, 2023 - ncbi.nlm.nih.gov
Electronic health records (EHR) data contain rich information about patients' health
conditions including diagnosis, procedures, medications and etc., which have been widely …

Spatiotemporal-aware session-based recommendation with graph neural networks

Y Li, C Gao, X Du, H Wei, H Luo, D Jin… - Proceedings of the 31st …, 2022 - dl.acm.org
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 …

User consumption intention prediction in meituan

Y Ping, C Gao, T Liu, X Du, H Luo, D Jin… - Proceedings of the 27th …, 2021 - dl.acm.org
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 …

MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings

Y Khaokaew, H Xue, FD Salim - Proceedings of the ACM on Interactive …, 2024 - dl.acm.org
In recent years, predicting mobile app usage has become increasingly important for areas
like app recommendation, user behaviour analysis, and mobile resource management …

NEON: Living Needs Prediction System in Meituan

X Lan, C Gao, S Wen, X Chen, Y Che… - Proceedings of the 29th …, 2023 - dl.acm.org
Living needs refer to the various needs in human's daily lives for survival and well-being,
including food, housing, entertainment, etc. At life service platforms that connect users to …