A cost-effective recommender system for taxi drivers

M Qu, H Zhu, J Liu, G Liu, H Xiong - Proceedings of the 20th ACM …, 2014 - dl.acm.org
The GPS technology and new forms of urban geography have changed the paradigm for
mobile services. As such, the abundant availability of GPS traces has enabled new ways of …

Mobile app recommendations with security and privacy awareness

H Zhu, H Xiong, Y Ge, E Chen - Proceedings of the 20th ACM SIGKDD …, 2014 - dl.acm.org
With the rapid prevalence of smart mobile devices, the number of mobile Apps available has
exploded over the past few years. To facilitate the choice of mobile Apps, existing mobile …

Scalable recommendation with social contextual information

M Jiang, P Cui, F Wang, W Zhu… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Exponential growth of information generated by online social networks demands effective
and scalable recommender systems to give useful results. Traditional techniques become …

Mining mobile user preferences for personalized context-aware recommendation

H Zhu, E Chen, H Xiong, K Yu, H Cao… - ACM Transactions on …, 2014 - dl.acm.org
Recent advances in mobile devices and their sensing capabilities have enabled the
collection of rich contextual information and mobile device usage records through the device …

Cross-platform app recommendation by jointly modeling ratings and texts

D Cao, X He, L Nie, X Wei, X Hu, S Wu… - ACM Transactions on …, 2017 - dl.acm.org
Over the last decade, the renaissance of Web technologies has transformed the online world
into an application (App) driven society. While the abundant Apps have provided great …

Discovery of ranking fraud for mobile apps

H Zhu, H Xiong, Y Ge, E Chen - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Ranking fraud in the mobile App market refers to fraudulent or deceptive activities which
have a purpose of bumping up the Apps in the popularity list. Indeed, it becomes more and …

Personalized app recommendation based on app permissions

M Peng, G Zeng, Z Sun, J Huang, H Wang, G Tian - World Wide Web, 2018 - Springer
With the development of science and technology, the popularity of smart phones has made
exponential growth in mobile phone application market. How to help users to select …

PEVRM: probabilistic evolution based version recommendation model for mobile applications

M Maheswari, S Geetha, SS Kumar, M Karuppiah… - IEEE …, 2021 - ieeexplore.ieee.org
Traditional recommendation approaches for the mobile Apps basically depend on the Apps
related features. Now a days many users are in quench of Apps recommendation based on …

A survey of context-aware mobile recommendations

Q Liu, H Ma, E Chen, H Xiong - International Journal of Information …, 2013 - World Scientific
Mobile recommender systems target on recommending the right product or information to
the right mobile users at anytime and anywhere. It is well known that the contextual …

Mobile app classification with enriched contextual information

H Zhu, E Chen, H Xiong, H Cao… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
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 …