Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support
Data Mining and Knowledge Discovery
A Framework for Generating Network-Based Moving Objects
Geoinformatica
ICDE '95 Proceedings of the Eleventh 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
Real-Time Traffic Updates in Moving Objects Databases
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Time-series prediction with applications to traffic and moving objects databases
Proceedings of the 3rd ACM international workshop on Data engineering for wireless and mobile access
Prediction and indexing of moving objects with unknown motion patterns
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
TrajPattern: mining sequential patterns from imprecise trajectories of mobile objects
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Mining Frequent Trajectories of Moving Objects for Location Prediction
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Location prediction within the mobility data analysis environment DAEDALUS
Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
Hotspot district trajectory prediction
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Semantic trajectory mining for location prediction
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
TMC-pattern: holistic trajectory extraction, modeling and mining
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
A “semi-lazy” approach to probabilistic path prediction in dynamic environments
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining geographic-temporal-semantic patterns in trajectories for location prediction
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Recent advances in wireless sensors and position technology provide us with unprecedent amount of moving object data. The volume of geospatial data gathered from moving objects defies human ability to analyze the stream of input data. Therefore, new methods for mining and digesting of moving object data are urgently needed. One of the popular services available for moving objects is the prediction of the unknown location of an object. In this paper we present a new method for predicting the location of a moving object. Our method uses the past trajectory of the object and combines it with movement rules discovered in the moving objects database. Our original contribution includes the formulation of the location prediction model, the design of an efficient algorithm for mining movement rules, the proposition of four strategies for movement rule matching with respect to a given object trajectory, and the experimental evaluation of the proposed model.