A road network embedding technique for k-nearest neighbor search in moving object databases
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Aggregate Nearest Neighbor Queries in Road Networks
IEEE Transactions on Knowledge and Data Engineering
Distance indexing on road networks
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Efficient Approximation of Spatial Network Queries using the M-Tree with Road Network Embedding
SSDBM '07 Proceedings of the 19th International Conference on Scientific and Statistical Database Management
Single-Source multi-target a* algorithm for POI queries on road network
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
Aggregate nearest neighbor search methods using SSMTA* algorithm on road-network
ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
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Aggregate K Nearest Neighbor (AKNN) queries are problematic when performed within spatial networks. While simpler network queries may be solved by a single network traversal search, the AKNN requires a large number costly network distance computations to completely compute results. The M-Tree index, when used with Road Network Embedding, provides an efficient alternative which can return estimates of the AKNN results. The M-Tree index can then be used as a filter for AKNN results by quickly computing a superset of the query results. The final AKNN query results can be computed by sorting the results from the M-Tree. In comparison to Incremental Euclidean Restriction (IER), the M-Tree reduces the overall query processing time and the total number of necessary network distance computations required to complete a query. In addition, the M-Tree filtering method is tunable to allow increasing performance at the expense of accuracy, making it suitable for a wide variety of applications.