Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications
Data Mining and Knowledge Discovery
GeoNotes: Social and Navigational Aspects of Location-Based Information Systems
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
Learning Significant Locations and Predicting User Movement with GPS
ISWC '02 Proceedings of the 6th IEEE International Symposium on Wearable Computers
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
Social matching: A framework and research agenda
ACM Transactions on Computer-Human Interaction (TOCHI)
An experiment in discovering personally meaningful places from location data
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Extraction of social context and application to personal multimedia exploration
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Discovering personally meaningful places: An interactive clustering approach
ACM Transactions on Information Systems (TOIS)
Geographic `Place' and `Community Information' Preferences
Computer Supported Cooperative Work
Identifying Meaningful Places: The Non-parametric Way
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
Mining periodic patterns in spatio-temporal sequences at different time granularities
Intelligent Data Analysis
Using Context Annotated Mobility Profiles to Recruit Data Collectors in Participatory Sensing
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Geographically-typed semantic schema matching
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Biketastic: sensing and mapping for better biking
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Toward a common model and a markup language for personal gazetteers
Proceedings of the 2nd ACM International Workshop on Hot Topics in Planet-scale Measurement
A visual analytics system for financial time-series data
Proceedings of the 3rd International Symposium on Visual Information Communication
Show me how you move and I will tell you who you are
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS
Personal data vaults: a locus of control for personal data streams
Proceedings of the 6th International COnference
Enhanced geographically typed semantic schema matching
Web Semantics: Science, Services and Agents on the World Wide Web
Show Me How You Move and I Will Tell You Who You Are
Transactions on Data Privacy
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
How do people's concepts of place relate to physical locations?
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
CityVoyager: an outdoor recommendation system based on user location history
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
Recruitment framework for participatory sensing data collections
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
Next place prediction using mobility Markov chains
Proceedings of the First Workshop on Measurement, Privacy, and Mobility
Detecting pedestrian flocks by fusion of multi-modal sensors in mobile phones
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Personal routine visualization using mobile devices
Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia
Lifestreams: a modular sense-making toolset for identifying important patterns from everyday life
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
| Hi-index | 0.00 |
Personal gazetteers record individuals' most important places, such as home, work, grocery store, etc. Using personal gazetteers in location-aware applications offers additional functionality and improves the user experience. However, systems then need some way to acquire them. This paper explores the use of novel semi-automatic techniques to discover gazetteers from users' travel patterns (time-stamped location data). There has been previous work on this problem, e.g., using ad hoc algorithms [13]or K-Means clustering[4]; however, both approaches have shortcomings. This paper explores a deterministic, density-based clustering algorithm that also uses temporal techniques to reduce the number of uninteresting places that are discovered. We introduce a general framework for evaluating personal gazetteer discovery algorithms and use it to demonstrate the advantages of our algorithm over previous approaches.