The selective travelling salesman problem
Discrete Applied Mathematics - Southampton conference on combinatorial optimization, April 1987
OPTICS: ordering points to identify the clustering structure
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
A Recursive Greedy Algorithm for Walks in Directed Graphs
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Generating summaries and visualization for large collections of geo-referenced photographs
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
World explorer: visualizing aggregate data from unstructured text in geo-referenced collections
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Digital Footprinting: Uncovering Tourists with User-Generated Content
IEEE Pervasive Computing
Proceedings of the 18th international conference on World wide web
Iterated local search for the team orienteering problem with time windows
Computers and Operations Research
Visual summaries of popular landmarks from community photo collections
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Constructing a landmark identification system for geo-tagged photographs based on web data analysis
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Automatic construction of travel itineraries using social breadcrumbs
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Photo2Trip: generating travel routes from geo-tagged photos for trip planning
Proceedings of the international conference on Multimedia
IV '10 Proceedings of the 2010 14th International Conference Information Visualisation
Research and applications on georeferenced multimedia: a survey
Multimedia Tools and Applications
The City Trip Planner: An expert system for tourists
Expert Systems with Applications: An International Journal
Interactive itinerary planning
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Personalized travel recommendation by mining people attributes from community-contributed photos
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Real-time routing with OpenStreetMap data
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Mining Travel Patterns from Geotagged Photos
ACM Transactions on Intelligent Systems and Technology (TIST)
GPSView: A scenic driving route planner
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Using social media to find places of interest: a case study
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information
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By utilizing large amount of crowd volunteered geo-tagged photos, existing research can successfully discover landmarks or attractive areas, mine travel patterns, find classical travel routes and recommend travel destinations or routes for inexperienced tourists. However, few of them focuses on a complicated real-life travel planning problem--planning multi-day and multi-stay (different places of accommodation) travel for tourist. By integrating new techniques in data mining and operational research, we develop a novel travel planning system to design multi-day and multi-stay travel plans based on geo-tagged photos. Specifically, a modified Iterated Local Search heuristic algorithm is developed to find an approximate optimal solution for the multi-day and multi-stay travel planning problem using points of interests (POIs) and recurrence weights between POIs in a travel graph model, which are discovered from photos. To demonstrate the feasibility of this approach, we retrieved geo-tagged photos in Australia from the photo sharing website Panoromia.com to design experimental multi-day and multi-stay travel plans for tourists. The travel patterns that are mined using flow-mapping technique at different geographical scales are used to evaluate the experimental results.