Modeling Users’ Behavior from Large Scale Smartphone Data Collection
Journal Title: EAI Endorsed Transactions on Context-aware Systems and Applications - Year 2016, Vol 3, Issue 10
Abstract
A large volume of research in ubiquitous systems has been devoted to using data, that has been sensed from users’ smartphones, to infer their current high level context and activities. However, mining users’ diverse longitudinal behavioral patterns, which can enable exciting new context-aware applications, has not received much attention. In this paper, we focus on learning and identifying such behavioral patterns from large-scale data collected from users’ smartphones. To this end, we develop a unified infrastructure and implement several novel approaches for building diverse behavioral models of users. Examples of generated models include classifying users’ semantic places and predicting their availability for accepting calls etc. We evaluate our work on real-world data of 200 users, from the DeviceAnalyzer dataset, consisting of 365 million data points and show that our algorithms and approaches can model user behavior with high accuracy and outperform existing approaches.
Authors and Affiliations
Preeti Bhargava, Ashok Agrawala
Keywords
Related Articles
- EP ID EP45785
- DOI http://dx.doi.org/10.4108/eai.12-9-2016.151677
- Views 239
- Downloads 0
Holistic Personas for Designers of a Context-Aware Accounting Information Systems e-Learning Application
E-learning systems have been increasingly used to train and empower employees to take a more active role in the creation and dissemination of system knowledge, when, either new systems are installed, or existing systems...
Applying Log Data to Context-Awareness in Home Network System
In the conventional context-aware services of the home network system (HNS), every context has been defined by current (or recent) situations only. Considering past situations in a house would significantly extend the ex...
Clustering the objective interestingness measures based on tendency of variation in statistical implications
In recent years, the research cluster of objective interestingness measures has rapidly developed in order to assist users to choose the appropriate measure for their application. Researchers in this field mainly focus o...
Mobile Agent Communication in Highly Dynamic Networks: A Self-Adaptive Architecture inspired by the Honey Bee Colony
Communication is considered as a building block for mobile agent systems. In highly dynamic networks, thanks to environmental stimuli such as changes in connection quality and network topology, performance of communicati...
Bootstrapped Discovery and Ranking of Relevant Services and Information in Context-aware Systems
A context-aware system uses context to provide relevant information and services to the user, where relevancy depends on the user’s situation. This relevant information could include a wide range of heterogeneous content...