"I'm waiting where we met last time": exploring everyday positioning practices to inform design
Proceedings of the third Nordic conference on Human-computer interaction
Experiences with place lab: an open source toolkit for location-aware computing
Proceedings of the 28th international conference on Software engineering
Discovering personally meaningful places: An interactive clustering approach
ACM Transactions on Information Systems (TOIS)
AniDiary: Daily Cartoon-Style Diary Exploits Bayesian Networks
IEEE Pervasive Computing
BeTelGeuse: a tool for Bluetooth data gathering
Proceedings of the ICST 2nd international conference on Body area networks
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
Inferring User Context from Spatio-Temporal Pattern Mining for Mobile Application Services
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
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Current mobile phones provide GSM cell information and many devices also support GPS or WiFi-based location information. A problem with raw location data is that it does not provide semantic information, which makes it hard to integrate location-awareness into applications. Moreover, to understand what kind of location information is important to users, researchers currently need to perform time consuming user studies. In this paper we introduce SerPens, a tool that enables gathering semantically enriched location information on personal devices. The main novelty of SerPens is that it enables users to share and gather semantic information in a collaborative fashion. The label information is tied to a taxonomy and is accessible to applications. SerPens has been developed on top of BeTelGeuse, a Bluetooth-based data gathering tool for J2ME compatible devices.