Introduction to algorithms
CCAM: A Connectivity-Clustered Access Method for Networks and Network Computations
IEEE Transactions on Knowledge and Data Engineering
Computing the shortest path: A search meets graph theory
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Query processing in spatial network databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
The optimal sequenced route query
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Merging and Filtering Algorithms for Approximate String Searches
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Keyword Search on Spatial Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Keyword Search in Spatial Databases: Towards Searching by Document
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient approximate search on string collections
Proceedings of the VLDB Endowment
Efficient retrieval of the top-k most relevant spatial web objects
Proceedings of the VLDB Endowment
Supporting location-based approximate-keyword queries
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Collective spatial keyword querying
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
On trip planning queries in spatial databases
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Keyword-aware optimal route search
Proceedings of the VLDB Endowment
Aggregate keyword routing in spatial database
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Elastic and effective spatio-temporal query processing scheme on Hadoop
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
Top-K nearest keyword search on large graphs
Proceedings of the VLDB Endowment
| Hi-index | 0.01 |
For GIS data situated on a road network, shortest path search is a basic operation. In practice, however, users are often interested at routing when certain constraints on the textual information have been also incorporated. This work complements the standard shortest path search with multiple keywords and an approximate string similarity function, where the goal is to find the shortest path that passes through at least one matching object per keyword; we dub this problem the multi-approximate-keyword routing (MAKR) query. We present both exact and approximate solutions. When the number κ of query keywords is small (e.g., κ ≤ 6), the exact solution works efficiently. However, when κ increases, it becomes increasingly expensive (especially on large GIS data). In this case, our approximate methods achieve superb query efficiency, excellent scalability, and high approximation quality, as indicated in our extensive experiments on large, real datasets (up to 2 million points on road networks with hundreds of thousands of nodes and edges). We also prove that one approximate method has a κ-approximation in the worst case.