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
SerPens: a tool for semantically enriched location information on personal devices
BodyNets '08 Proceedings of the ICST 3rd international conference on Body area networks
Social and Personal Context Modeling for Contact List Recommendation on Mobile Device
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Mining and Visualizing Mobile Social Network Based on Bayesian Probabilistic Model
UIC '09 Proceedings of the 6th International Conference on Ubiquitous Intelligence and Computing
ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors
Expert Systems with Applications: An International Journal
Extracting meaningful contexts from mobile life log
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Exploiting mobile contexts for Petri-net to generate a story in cartoons
Applied Intelligence
"All-about" diaries: concepts and experiences
Proceedings of the 5th International Conference on Communication System Software and Middleware
"Life portal": an information access scheme based on life logs
HCII'11 Proceedings of the 1st international conference on Human interface and the management of information: interacting with information - Volume Part II
Visualization and management of u-contents for ubiquitous VR
Proceedings of the 2011 international conference on Virtual and mixed reality: systems and applications - Volume Part II
Exploiting indoor location and mobile information for context-awareness service
Information Processing and Management: an International Journal
Expert Systems with Applications: An International Journal
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
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Owing to the advance of ubiquitous computing technology, various information sources make the events of a given user's daily life readily available. Mobile devices such as cell phones, smart phones, and PDAs let users capture rich media with ease and store personal information such as context, schedules, short messages, photos, and videos. We can regard usage information and stored multimedia content as relevant evidence for inferring a given user's daily actions. The AniDiary (Anywhere Diary) system summarizes a given user's daily life with as a cartoon-style diary. Because showing all the events for a day isn't appropriate, landmark (memorable) events are automatically detected by modeling the cause-effect relationships of various events with Bayesian networks. The system then converts the events into cartoon images for a diary. Experimental results on synthetic and real data show that AniDiary provides an efficient, user-friendly way to summarize the user's daily life.