Gray Codes for Partial Match and Range Queries
IEEE Transactions on Software Engineering
Fractals for secondary key retrieval
PODS '89 Proceedings of the eighth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
SAC '98 Proceedings of the 1998 ACM symposium on Applied Computing
A class of data structures for associative searching
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries
Proceedings of the 27th International Conference on Very Large Data Bases
Roads, codes, and spatiotemporal queries
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Query processing in spatial network databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Information Sciences: an International Journal
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Due to the rapid development in mobile communication technologies, the usage of mobile devices such as cell phone or PDA becomes increasingly popular. As different devices require different applications, various new services are being developed to satisfy the needs. One of the popular services under heavy demand is the Location-based Service (LBS) that exploits the spatial information of moving objects per temporal changes. In order to support LBS efficiently, it is necessary to be able to index and query well a large amount of spatio-temporal information of moving objects. Therefore, in this paper, we investigate how such location information of moving objects can be efficiently stored and indexed. In particular, we propose a novel location encoding method based on hierarchical administrative district information. Our proposal is different from conventional approaches where moving objects are often expressed as geometric points in two dimensional space, (x, y). Instead, in ours, moving objects are encoded as one dimensional points by both administrative district as well as road information. Our method is especially useful for monitoring traffic situation or tracing location of moving objects through approximate spatial queries.