Self-supervised human mobility learning for next location prediction and trajectory classification
Massive digital mobility data are accumulated nowadays due to the proliferation of location-
based service (LBS), which provides the opportunity of learning knowledge from human …
based service (LBS), which provides the opportunity of learning knowledge from human …
Fine-grained spatio-temporal distribution prediction of mobile content delivery in 5G ultra-dense networks
The 5G networks have extensively promoted the growth of mobile users and novel
applications, and with the skyrocketing user requests for a large amount of popular content …
applications, and with the skyrocketing user requests for a large amount of popular content …
Demystifying removed apps in ios app store
F Lin - arXiv preprint arXiv:2101.05100, 2021 - arxiv.org
With the popularity of mobile devices, mobile applications have become an essential part of
people's lives. To provide secure mobile application download channels for users, various …
people's lives. To provide secure mobile application download channels for users, various …
基于电信大数据的5G 网络海量用户复访行为预测模型
孙玉娣 - 电信科学, 2023 - infocomm-journal.com
5G 网络中的用户会产生大量的访问数据, 导致用户复访行为难以精准预测, 因此提出基于电信大
数据的5G 网络海量用户复访行为预测模型. 从电信大数据中提取用户上网历史行为特征数据 …
数据的5G 网络海量用户复访行为预测模型. 从电信大数据中提取用户上网历史行为特征数据 …
Large-scale trajectory prediction via relationship-aware adaptive hierarchical graph learning
Trajectory prediction is an important task that enables applications in many domains, such
as intelligent transportation systems and video analytics. Most existing methods either (i) …
as intelligent transportation systems and video analytics. Most existing methods either (i) …
Exploring Context Generalizability in Citywide Crowd Mobility Prediction: An Analytic Framework and Benchmark
Contextual features are important data sources for building citywide crowd mobility
prediction models. However, the difficulty of applying context lies in the unknown …
prediction models. However, the difficulty of applying context lies in the unknown …
Understanding diffusion of recurrent innovations
F Lin - arXiv preprint arXiv:2101.05094, 2021 - arxiv.org
The diffusion of innovations theory has been studied for years. Previous research efforts
mainly focus on key elements, adopter categories, and the process of innovation diffusion …
mainly focus on key elements, adopter categories, and the process of innovation diffusion …
: Cloud-Client Cooperative Deep Learning for Temporal Recommendation in the Post-GDPR Era
Mobile devices enable users to retrieve information at any time and any place. Considering
the occasional requirements and fragmentation usage pattern of mobile users, temporal …
the occasional requirements and fragmentation usage pattern of mobile users, temporal …