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A Time-Aware Personalized Point-of-Interest Recommendation via High-Order Tensor Factorization
Xin Li, Mingming Jiang, Huiting Hong, Lejian Liao
Article No.: 31
Recently, location-based services (LBSs) have been increasingly popular for people to experience new possibilities, for example, personalized point-of-interest (POI) recommendations that leverage on the overlapping of user trajectories to...
To address the difficulty in clipping articles from various mobile applications (apps), we propose a novel framework called UniClip, which allows a user to snap a screen of an article to save the whole article in one place. The key task of the...
User Modeling on Demographic Attributes in Big Mobile Social Networks
Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, Yang Yang
Article No.: 35
Users with demographic profiles in social networks offer the potential to understand the social principles that underpin our highly connected world, from individuals, to groups, to societies. In this article, we harness the power of network and...
Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts
Da Cao, Xiangnan He, Liqiang Nie, Xiaochi Wei, Xia Hu, Shunxiang Wu, Tat-Seng Chua
Article No.: 37
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 convenience, their sheer number also leads to severe information...
With the great popularity of mobile devices, the amount of mobile apps has grown at a more dramatic rate than ever expected. A technical challenge is how to recommend suitable apps to mobile users. In this work, we identify and focus on a unique...
Deriving User Preferences of Mobile Apps from Their Management Activities
Xuanzhe Liu, Wei Ai, Huoran Li, Jian Tang, Gang Huang, Feng Feng, Qiaozhu Mei
Article No.: 39
App marketplaces host millions of mobile apps that are downloaded billions of times. Investigating how people manage mobile apps in their everyday lives creates a unique opportunity to understand the behavior and preferences of mobile device...
Computing Urban Traffic Congestions by Incorporating Sparse GPS Probe Data and Social Media Data
Senzhang Wang, Xiaoming Zhang, Jianping Cao, Lifang He, Leon Stenneth, Philip S. Yu, Zhoujun Li, Zhiqiu Huang
Article No.: 40
Estimating urban traffic conditions of an arterial network with GPS probe data is a practically important while substantially challenging problem, and has attracted increasing research interests recently. Although GPS probe data is becoming a...
DeepMob: Learning Deep Knowledge of Human Emergency Behavior and Mobility from Big and Heterogeneous Data
Xuan Song, Ryosuke Shibasaki, Nicholos Jing Yuan, Xing Xie, Tao Li, Ryutaro Adachi
Article No.: 41
The frequency and intensity of natural disasters has increased significantly in recent decades, and this trend is expected to continue. Hence, understanding and predicting human evacuation behavior and mobility will play a vital role in planning...
Understanding the Purpose of Permission Use in Mobile Apps
Haoyu Wang, Yuanchun Li, Yao Guo, Yuvraj Agarwal, Jason I. Hong
Article No.: 43
Mobile apps frequently request access to sensitive data, such as location and contacts. Understanding the purpose of why sensitive data is accessed could help improve privacy as well as enable new kinds of access control. In this article, we...