Experiences of developing and deploying a context-aware tourist guide: the GUIDE project
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Maintaining knowledge about temporal intervals
Communications of the ACM
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Using proxy cache relocation to accelerate Web browsing in wireless/mobile communications
Proceedings of the 10th international conference on World Wide Web
Location based services in a wireless WAN using cellular digital packet data (CDPD)
Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access
Aggregation and comparison of trajectories
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Efficient Mining of Spatiotemporal Patterns
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
NAPA: Nearest Available Parking Lot Application
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Multidimensional data modeling for location-based services
The VLDB Journal — The International Journal on Very Large Data Bases
Bluetooth and WAP push based location-aware mobile advertising system
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Modeling, Storing, and Mining Moving Object Databases
IDEAS '04 Proceedings of the International Database Engineering and Applications Symposium
A data mining approach for location prediction in mobile environments
Data & Knowledge Engineering
Safety High Accuracy Context-Aware Matrix (CAM) Making Based on X.509 Proxy Certificate
ISA '09 Proceedings of the 3rd International Conference and Workshops on Advances in Information Security and Assurance
Context-aware personal route recognition
DS'11 Proceedings of the 14th international conference on Discovery science
Surrogate object based data mining for distributed mobile systems
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
A multi-layer data representation of trajectories in social networks based on points of interest
Proceedings of the twelfth international workshop on Web information and data management
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Convergence of location-aware devices, wireless communications, and geographic information system (GIS) functionalities has been enabling the deployment of a new generation of selective information disseminating services and location-based services (LBSs). Current LBSs use information about current locations of users to provide services, such as nearest features of interest, they request. Although the common computing strategy in LBSs benefits the users, there are additional benefits when future locations are predicted. One major advantage of location prediction is that it provides LBSs with extended resources, mainly time, to improve system reliability which in turn increases the users' confidence and the demand for LBSs. In this study, we propose a movement Rule-based Location Prediction method (RLP), to guess the user's future location for LBSs. Its performance is assessed with respect to precision and recall. In comparison with the previous technique, the prediction accuracy of ours is higher. With the proposed approach, we give an efficient support to the LBSs provider in monitoring user intelligently and sending information to user in a push-driven fashion. Apart from the support of timely and desired services and enhanced automation, the technique helps overcome some existing issues such as network flooding due to the massive tracking of users, the latencies of the positioning systems in providing and information delivery. Accordingly, the positioning is more reliable, which enables the service provider to effectively and efficiently offer location-based services with high frequency.