Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
ContextPhone: A Prototyping Platform for Context-Aware Mobile Applications
IEEE Pervasive Computing
IEEE Transactions on Mobile Computing
Petri Net-Based Episode Detection and Story Generation from Ubiquitous Life Log
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
Life Story Generation Using Mobile Context and Petri Net
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Modular Bayesian Network Learning for Mobile Life Understanding
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Landmark detection from mobile life log using a modular Bayesian network model
Expert Systems with Applications: An International Journal
Generating cartoon-style summary of daily life with multimedia mobile devices
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Mobile sync-application for life logging and high-level context using Bayesian network
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
Exploiting mobile contexts for Petri-net to generate a story in cartoons
Applied Intelligence
Exploiting indoor location and mobile information for context-awareness service
Information Processing and Management: an International Journal
Hi-index | 0.00 |
Mobile devices get to handle much information thanks to the convergence of diverse functionalities. Their environment has great potential of supporting customized services to the users because it can observe the meaningful and private information continually for a long time. However, most of the information has been generally ignored because of the limitations of mobile devices. In this paper, we propose a novel method that infers landmarks efficiently in order to overcome the problems. It uses an effective probabilistic model of Bayesian networks for analyzing various log data on the mobile environment, which is modularized to decrease the complexity. The proposed methods are evaluated with synthetic mobile log data generated.