Mining Interesting Locations and Travel Sequences from GPS Trajectories

1. Mining Interesting Locations and Travel Sequences from GPS Trajectories defense by Alok Rakkhit

2. Overview • Take GPS data of Multiple users to find travel sequences and interesting locations • That data can be used to help understanding of surrounding area and provide travel recommendations • Interesting places get many users and experienced users • Interest and user experience are region-related • Knowledge of Beijing doesn’t imply knowledge of New York

3. Architecture • Take raw data and determine locations (stay points) and travel paths • Combine users location histories and create Tree-Based Hierarchical Graph • Apply Hypertext Induced Topic Search to TBHG to infer location interest and user experience • Create travel recomendations based on the data

4. Data • 107 users tracked from May 2007 to October 2008 • Beijing plus 36 other Chinese cities, as well as cities in US, South Korea, and Japan • Stay point detection thresholds prevent inclusion of irrelevant locations (stopping at traffic lights, users’ homes and offices) • Clustering using density-based algorithm, OPTICS

5. Evaluation • 29 subjects, living in Beijing for over 6 years answered evaluation questions about the locations and paths • Baselines for locations were rank by count and by frequency • Baseline for paths were rank by count, by interests, and by experience

6. Results

7. GeoLife

8. Significance • Project GeoLife • Advantages of hierarchical system in understanding location data at multiple scales of resolution • Integrate social networking into real time location information • Apply location/user relationship to improve recommendation systems