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 …
Sequence-aware recommender systems
Recommender systems are one of the most successful applications of data mining and
machine-learning technology in practice. Academic research in the field is historically often …
machine-learning technology in practice. Academic research in the field is historically often …
Evaluation of session-based recommendation algorithms
Recommender systems help users find relevant items of interest, for example on e-
commerce or media streaming sites. Most academic research is concerned with approaches …
commerce or media streaming sites. Most academic research is concerned with approaches …
How age and gender affect smartphone usage
Smartphone usage is a hot topic in pervasive computing due to their popularity and personal
aspect. We present our initial results from analyzing how individual differences, such as …
aspect. We present our initial results from analyzing how individual differences, such as …
Personality research and assessment in the era of machine learning
The increasing availability of high–dimensional, fine–grained data about human behaviour,
gathered from mobile sensing studies and in the form of digital footprints, is poised to …
gathered from mobile sensing studies and in the form of digital footprints, is poised to …
Context-aware rule learning from smartphone data: survey, challenges and future directions
IH Sarker - Journal of Big Data, 2019 - Springer
Smartphones are considered as one of the most essential and highly personal devices of
individuals in our current world. Due to the popularity of context-aware technology and …
individuals in our current world. Due to the popularity of context-aware technology and …
Air: Attentional intention-aware recommender systems
The capability of extracting sequential patterns from the user-item interaction data is now
becoming a key feature of recommender systems. Though it is important to capture the …
becoming a key feature of recommender systems. Though it is important to capture the …
A survey of performance optimization for mobile applications
To ensure user satisfaction and success of mobile applications, it is important to provide
highly performant applications. This is particularly important for resource-constrained …
highly performant applications. This is particularly important for resource-constrained …
Customer lifetime value prediction using embeddings
We describe the Customer LifeTime Value (CLTV) prediction system deployed at ASOS.
com, a global online fashion retailer. CLTV prediction is an important problem in e …
com, a global online fashion retailer. CLTV prediction is an important problem in e …
Mining smartphone data for app usage prediction and recommendations: A survey
H Cao, M Lin - Pervasive and Mobile Computing, 2017 - Elsevier
Smartphones nowadays have become indispensable personal gadgets to support our
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …