SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Web3D '03 Proceedings of the eighth international conference on 3D Web technology
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
Mining people's trips from large scale geo-tagged photos
Proceedings of the international conference on Multimedia
Photo2Trip: generating travel routes from geo-tagged photos for trip planning
Proceedings of the international conference on Multimedia
Hi-index | 0.00 |
It has recently become a common practice for people to post their sightseeing experiences on weblogs (blogs). Their blog entries often contain valuable information for potential tourists, who can learn about various aspects not found on the official websites of sightseeing spots. Bloggers provide images, videos and texts regarding the places they visited. This implies that popular travel routes could be extracted according to the information available in blogs. In this paper, we describe a system that extracts typical visitor's travel routes based on blog entries and that presents multimedia content relevant to those routes. Typical travel routes are extracted by using a sequential pattern mining method. We also introduce a new user interface for presenting multimedia content along the route in a proactive manner. The system works as an automatically generated tour guide accessible from a PC or a mobile device.