Understanding and Using Context
Personal and Ubiquitous Computing
Context Awareness and Mobile Phones
Personal and Ubiquitous Computing
Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld 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
MyLifeBits: a personal database for everything
Communications of the ACM - Personal information management
Context-Aware Artifacts: Two Development Approaches
IEEE Pervasive Computing
AniDiary: Daily Cartoon-Style Diary Exploits Bayesian Networks
IEEE Pervasive Computing
Rule-Based WiFi Localization Methods
EUC '08 Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing - Volume 01
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
Exploiting mobile contexts for Petri-net to generate a story in cartoons
Applied Intelligence
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
A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques
Information Processing and Management: an International Journal
Human activity recognition with trajectory data in multi-floor indoor environment
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
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Personal mobile devices such as cellular phones, smart phones and PMPs have advanced incredibly in the past decade. The mobile technologies make research on the life log and user-context awareness feasible. In other words, sensors in mobile devices can collect the variety of user's information, and various works have been conducted using that information. Most of works used a user's location information as the most useful clue to recognize the user context. However, the location information in the conventional works usually depends on a GPS receiver that has limited function, because it cannot localize a person in a building and thus lowers the performance of the user-context awareness. This paper develops a system to solve such problems and to infer a user's hidden information more accurately using Bayesian network and indoor-location information. Also, this paper presents a new technique for localization in a building using a decision tree and signals for the Wireless LAN because the decision tree has many advantages which outweigh other localization techniques.