Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
mPATH: An Interactive Visualization Framework for Behavior History
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1
Using Location for Personalized POI Recommendations in Mobile Environments
SAINT '06 Proceedings of the International Symposium on Applications on Internet
A mobile application framework for the geospatial web
Proceedings of the 16th international conference on World Wide Web
Exploiting real world knowledge in ubiquitous applications
Personal and Ubiquitous Computing
GeoLife: Managing and Understanding Your Past Life over Maps
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Understanding mobility based on GPS data
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
Mining correlation between locations using human location history
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
CityVoyager: an outdoor recommendation system based on user location history
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
Predestination: inferring destinations from partial trajectories
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Location-based recommendation system using Bayesian user's preference model in mobile devices
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
Mining GPS traces to recommend common meeting points
Proceedings of the 16th International Database Engineering & Applications Sysmposium
| Hi-index | 0.00 |
It is possible to obtain fine grained location information fairly easily using Global Positioning System (GPS) enabled devices. It becomes easy to track an individual's location and trace her trajectory using such devices. By aggregating this data and analyzing multiple users' trajectory a lot of useful information can be extracted. In this paper, we aim to analyze aggregate GPS information of multiple users to mine a list of interesting locations and rank them. By interesting locations we mean the geographical locations visited by several users. It can be an office, university, historical place, a good restaurant, a shopping complex, a stadium, etc. To achieve this various relational algebra operations and statistical operations are applied on the GPS trajectory data of multiple users. The end result is a ranked list of interesting locations. We show the results of applying our methods on a large real life GPS dataset of sixty two users collected over a period of two years.