Statistical complexity of the power method for Markov chains
Journal of Complexity
Cyberguide: a mobile context-aware tour guide
Wireless Networks - Special issue: mobile computing and networking: selected papers from MobiCom '96
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Extracting places from traces of locations
ACM SIGMOBILE Mobile Computing and Communications Review
A mobile application framework for the geospatial web
Proceedings of the 16th international conference on World Wide Web
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Adaptive fastest path computation on a road network: a traffic mining approach
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Dynamics-aware similarity of moving objects trajectories
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Learning transportation mode from raw gps data for geographic applications on the web
Proceedings of the 17th international conference on World Wide Web
A Flexible Spatio-Temporal Indexing Scheme for Large-Scale GPS Track Retrieval
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Continuous Clustering of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
On efficiently searching trajectories and archival data for historical similarities
Proceedings of the VLDB Endowment
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering
Proceedings of the VLDB Endowment
Scalable processing of trajectory-based queries in space-partitioned moving objects databases
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Mining user similarity based on location history
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
TripTip: a trip planning service with tag-based recommendation
CHI '09 Extended Abstracts on Human Factors in Computing Systems
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
A Hybrid Prediction Model for Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Monitoring minimum cost paths on road networks
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Hidden Markov map matching through noise and sparseness
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Map-matching for low-sampling-rate GPS trajectories
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Collaborative location and activity recommendations with GPS history data
Proceedings of the 19th international conference on World wide web
Searching trajectories by locations: an efficiency study
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Automatic construction of travel itineraries using social breadcrumbs
Proceedings of the 21st ACM conference on Hypertext and hypermedia
PATS: A Framework of Pattern-Aware Trajectory Search
MDM '10 Proceedings of the 2010 Eleventh International Conference on Mobile Data Management
Mining periodic behaviors for moving objects
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic construction and multi-level visualization of semantic trajectories
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Automatic construction and multi-level visualization of semantic trajectories
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Photo2Trip: generating travel routes from geo-tagged photos for trip planning
Proceedings of the international conference on Multimedia
Learning travel recommendations from user-generated GPS traces
ACM Transactions on Intelligent Systems and Technology (TIST)
Mining significant semantic locations from GPS data
Proceedings of the VLDB Endowment
Smart itinerary recommendation based on user-generated GPS trajectories
UIC'10 Proceedings of the 7th international conference on Ubiquitous intelligence and computing
SeMiTri: a framework for semantic annotation of heterogeneous trajectories
Proceedings of the 14th International Conference on Extending Database Technology
CityVoyager: an outdoor recommendation system based on user location history
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
A hybrid model and computing platform for spatio-semantic trajectories
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Advanced traveler information system for Hyderabad City
IEEE Transactions on Intelligent Transportation Systems
Social itinerary recommendation from user-generated digital trails
Personal and 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
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With the popularity of positioning devices, Web 2.0 technology, and trip sharing services, many users are willing to log and share their trips on the Web. Thus, trip planning Web sites are able to provide some new services by inferring Regions-Of-Interest (ROIs) and recommending popular travel routes from trip trajectories. We argue that simply providing some travel routes consisting of popular ROIs to users is not sufficient. To tour around a wide geographical area, for example, a city, some users may prefer a trip to visit as many ROIs as possible, while others may like to stop by only a few ROIs for an in-depth visit. We refer to a trip fitting the former user group as an in-breadth trip and a trip suitable for the latter user group as an in-depth trip. Prior studies on trip planning have focused on mining ROIs and travel routes without considering these different preferences. In this article, given a spatial range and a user preference of depth/breadth specified by a user, we develop a Pattern-Aware Trajectory Search (PATS) framework to retrieve the top K trajectories passing through popular ROIs. PATS is novel because the returned travel trajectories, discovered from travel patterns hidden in trip trajectories, may represent the most valuable travel experiences of other travelers fitting the user's trip preference in terms of depth or breadth. The PATS framework comprises two components: travel behavior exploration and trajectory search. The travel behavior exploration component determines a set of ROIs along with their attractive scores by considering not only the popularity of the ROIs but also the travel sequential relationships among the ROIs. To capture the travel sequential relationships among ROIs and to derive their attractive scores, a user movement graph is constructed. For the trajectory search component of PATS, we formulate two trajectory score functions, the depth-trip score function and the breadth-trip score function, by taking into account the number of ROIs in a trajectory and their attractive scores. Accordingly, we propose an algorithm, namely, Bounded Trajectory Search (BTS), to efficiently retrieve the top K trajectories based on the two trajectory scores. The PATS framework is evaluated by experiments and user studies using a real dataset. The experimental results demonstrate the effectiveness and the efficiency of the proposed PATS framework.