Bayesian Network Refinement Via Machine Learning Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Context-Aware Telephony Over WAP
Personal and Ubiquitous Computing
Decision Making and Uncertainty Management in a 3D Reconstruction System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
SenSay: A Context-Aware Mobile Phone
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
MIThril 2003: Applications and Architecture
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
What we talk about when we talk about context
Personal and Ubiquitous Computing
Passive capture and ensuing issues for a personal lifetime store
Proceedings of the the 1st ACM workshop on Continuous archival and retrieval of personal experiences
ContextPhone: A Prototyping Platform for Context-Aware Mobile Applications
IEEE Pervasive Computing
IEEE Transactions on Mobile Computing
Full Bayesian network classifiers
ICML '06 Proceedings of the 23rd international conference on Machine learning
Scalable Parallel Implementation of Exact Inference in Bayesian Networks
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Managing Context Information in Mobile Devices
IEEE Pervasive Computing
Learning hierarchical bayesian networks for large-scale data analysis
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Modular bayesian networks for inferring landmarks on mobile daily life
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Active and dynamic information fusion for multisensor systems with dynamic bayesian networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Active affective State detection and user assistance with dynamic bayesian networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A probabilistic framework for modeling and real-time monitoring human fatigue
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Human activity inference using hierarchical bayesian network in mobile contexts
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Fusion of modular bayesian networks for context-aware decision making
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Understanding and prediction of mobile application usage for smart phones
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Automatic image tagging using two-layered Bayesian networks and mobile data from smart phones
Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia
A mobile picture tagging system using tree-structured layered Bayesian networks
Mobile Information Systems
| Hi-index | 12.05 |
Mobile devices can now handle a great deal of information thanks to the convergence of diverse functionalities. Mobile environments have already shown great potential in terms of providing customized services to users because they can record meaningful and private information continually for long periods of time. Until now, most of this information has been generally ignored because of the limitations of mobile devices in terms of power, memory capacity and speed. In this paper, we propose a novel method that efficiently infers landmarks for users to overcome these problems. This method uses an effective probabilistic Bayesian network model for analyzing various kinds of log data in mobile environments, which were modularized in this paper to decrease complexity. We also present a cooperative inference method, and the proposed methods were evaluated with mobile log data generated and collected in the real world.